Actual source code: mpiaij.c
petsc-3.12.0 2019-09-29
1: #include <../src/mat/impls/aij/mpi/mpiaij.h>
2: #include <petsc/private/vecimpl.h>
3: #include <petsc/private/vecscatterimpl.h>
4: #include <petsc/private/isimpl.h>
5: #include <petscblaslapack.h>
6: #include <petscsf.h>
7: #include <petsc/private/hashmapi.h>
9: /*MC
10: MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices.
12: This matrix type is identical to MATSEQAIJ when constructed with a single process communicator,
13: and MATMPIAIJ otherwise. As a result, for single process communicators,
14: MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation() is supported
15: for communicators controlling multiple processes. It is recommended that you call both of
16: the above preallocation routines for simplicity.
18: Options Database Keys:
19: . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions()
21: Developer Notes:
22: Subclasses include MATAIJCUSP, MATAIJCUSPARSE, MATAIJPERM, MATAIJSELL, MATAIJMKL, MATAIJCRL, and also automatically switches over to use inodes when
23: enough exist.
25: Level: beginner
27: .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ, MATMPIAIJ
28: M*/
30: /*MC
31: MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices.
33: This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator,
34: and MATMPIAIJCRL otherwise. As a result, for single process communicators,
35: MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported
36: for communicators controlling multiple processes. It is recommended that you call both of
37: the above preallocation routines for simplicity.
39: Options Database Keys:
40: . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions()
42: Level: beginner
44: .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL
45: M*/
47: static PetscErrorCode MatPinToCPU_MPIAIJ(Mat A,PetscBool flg)
48: {
49: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
53: #if defined(PETSC_HAVE_CUDA) || defined(PETSC_HAVE_VIENNACL)
54: A->pinnedtocpu = flg;
55: #endif
56: if (a->A) {
57: MatPinToCPU(a->A,flg);
58: }
59: if (a->B) {
60: MatPinToCPU(a->B,flg);
61: }
62: return(0);
63: }
66: PetscErrorCode MatSetBlockSizes_MPIAIJ(Mat M, PetscInt rbs, PetscInt cbs)
67: {
69: Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data;
72: if (mat->A) {
73: MatSetBlockSizes(mat->A,rbs,cbs);
74: MatSetBlockSizes(mat->B,rbs,1);
75: }
76: return(0);
77: }
79: PetscErrorCode MatFindNonzeroRows_MPIAIJ(Mat M,IS *keptrows)
80: {
81: PetscErrorCode ierr;
82: Mat_MPIAIJ *mat = (Mat_MPIAIJ*)M->data;
83: Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data;
84: Mat_SeqAIJ *b = (Mat_SeqAIJ*)mat->B->data;
85: const PetscInt *ia,*ib;
86: const MatScalar *aa,*bb;
87: PetscInt na,nb,i,j,*rows,cnt=0,n0rows;
88: PetscInt m = M->rmap->n,rstart = M->rmap->rstart;
91: *keptrows = 0;
92: ia = a->i;
93: ib = b->i;
94: for (i=0; i<m; i++) {
95: na = ia[i+1] - ia[i];
96: nb = ib[i+1] - ib[i];
97: if (!na && !nb) {
98: cnt++;
99: goto ok1;
100: }
101: aa = a->a + ia[i];
102: for (j=0; j<na; j++) {
103: if (aa[j] != 0.0) goto ok1;
104: }
105: bb = b->a + ib[i];
106: for (j=0; j <nb; j++) {
107: if (bb[j] != 0.0) goto ok1;
108: }
109: cnt++;
110: ok1:;
111: }
112: MPIU_Allreduce(&cnt,&n0rows,1,MPIU_INT,MPI_SUM,PetscObjectComm((PetscObject)M));
113: if (!n0rows) return(0);
114: PetscMalloc1(M->rmap->n-cnt,&rows);
115: cnt = 0;
116: for (i=0; i<m; i++) {
117: na = ia[i+1] - ia[i];
118: nb = ib[i+1] - ib[i];
119: if (!na && !nb) continue;
120: aa = a->a + ia[i];
121: for (j=0; j<na;j++) {
122: if (aa[j] != 0.0) {
123: rows[cnt++] = rstart + i;
124: goto ok2;
125: }
126: }
127: bb = b->a + ib[i];
128: for (j=0; j<nb; j++) {
129: if (bb[j] != 0.0) {
130: rows[cnt++] = rstart + i;
131: goto ok2;
132: }
133: }
134: ok2:;
135: }
136: ISCreateGeneral(PetscObjectComm((PetscObject)M),cnt,rows,PETSC_OWN_POINTER,keptrows);
137: return(0);
138: }
140: PetscErrorCode MatDiagonalSet_MPIAIJ(Mat Y,Vec D,InsertMode is)
141: {
142: PetscErrorCode ierr;
143: Mat_MPIAIJ *aij = (Mat_MPIAIJ*) Y->data;
144: PetscBool cong;
147: MatHasCongruentLayouts(Y,&cong);
148: if (Y->assembled && cong) {
149: MatDiagonalSet(aij->A,D,is);
150: } else {
151: MatDiagonalSet_Default(Y,D,is);
152: }
153: return(0);
154: }
156: PetscErrorCode MatFindZeroDiagonals_MPIAIJ(Mat M,IS *zrows)
157: {
158: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)M->data;
160: PetscInt i,rstart,nrows,*rows;
163: *zrows = NULL;
164: MatFindZeroDiagonals_SeqAIJ_Private(aij->A,&nrows,&rows);
165: MatGetOwnershipRange(M,&rstart,NULL);
166: for (i=0; i<nrows; i++) rows[i] += rstart;
167: ISCreateGeneral(PetscObjectComm((PetscObject)M),nrows,rows,PETSC_OWN_POINTER,zrows);
168: return(0);
169: }
171: PetscErrorCode MatGetColumnNorms_MPIAIJ(Mat A,NormType type,PetscReal *norms)
172: {
174: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)A->data;
175: PetscInt i,n,*garray = aij->garray;
176: Mat_SeqAIJ *a_aij = (Mat_SeqAIJ*) aij->A->data;
177: Mat_SeqAIJ *b_aij = (Mat_SeqAIJ*) aij->B->data;
178: PetscReal *work;
181: MatGetSize(A,NULL,&n);
182: PetscCalloc1(n,&work);
183: if (type == NORM_2) {
184: for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) {
185: work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]*a_aij->a[i]);
186: }
187: for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) {
188: work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]*b_aij->a[i]);
189: }
190: } else if (type == NORM_1) {
191: for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) {
192: work[A->cmap->rstart + a_aij->j[i]] += PetscAbsScalar(a_aij->a[i]);
193: }
194: for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) {
195: work[garray[b_aij->j[i]]] += PetscAbsScalar(b_aij->a[i]);
196: }
197: } else if (type == NORM_INFINITY) {
198: for (i=0; i<a_aij->i[aij->A->rmap->n]; i++) {
199: work[A->cmap->rstart + a_aij->j[i]] = PetscMax(PetscAbsScalar(a_aij->a[i]), work[A->cmap->rstart + a_aij->j[i]]);
200: }
201: for (i=0; i<b_aij->i[aij->B->rmap->n]; i++) {
202: work[garray[b_aij->j[i]]] = PetscMax(PetscAbsScalar(b_aij->a[i]),work[garray[b_aij->j[i]]]);
203: }
205: } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType");
206: if (type == NORM_INFINITY) {
207: MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));
208: } else {
209: MPIU_Allreduce(work,norms,n,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));
210: }
211: PetscFree(work);
212: if (type == NORM_2) {
213: for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]);
214: }
215: return(0);
216: }
218: PetscErrorCode MatFindOffBlockDiagonalEntries_MPIAIJ(Mat A,IS *is)
219: {
220: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
221: IS sis,gis;
222: PetscErrorCode ierr;
223: const PetscInt *isis,*igis;
224: PetscInt n,*iis,nsis,ngis,rstart,i;
227: MatFindOffBlockDiagonalEntries(a->A,&sis);
228: MatFindNonzeroRows(a->B,&gis);
229: ISGetSize(gis,&ngis);
230: ISGetSize(sis,&nsis);
231: ISGetIndices(sis,&isis);
232: ISGetIndices(gis,&igis);
234: PetscMalloc1(ngis+nsis,&iis);
235: PetscArraycpy(iis,igis,ngis);
236: PetscArraycpy(iis+ngis,isis,nsis);
237: n = ngis + nsis;
238: PetscSortRemoveDupsInt(&n,iis);
239: MatGetOwnershipRange(A,&rstart,NULL);
240: for (i=0; i<n; i++) iis[i] += rstart;
241: ISCreateGeneral(PetscObjectComm((PetscObject)A),n,iis,PETSC_OWN_POINTER,is);
243: ISRestoreIndices(sis,&isis);
244: ISRestoreIndices(gis,&igis);
245: ISDestroy(&sis);
246: ISDestroy(&gis);
247: return(0);
248: }
250: /*
251: Distributes a SeqAIJ matrix across a set of processes. Code stolen from
252: MatLoad_MPIAIJ(). Horrible lack of reuse. Should be a routine for each matrix type.
254: Only for square matrices
256: Used by a preconditioner, hence PETSC_EXTERN
257: */
258: PETSC_EXTERN PetscErrorCode MatDistribute_MPIAIJ(MPI_Comm comm,Mat gmat,PetscInt m,MatReuse reuse,Mat *inmat)
259: {
260: PetscMPIInt rank,size;
261: PetscInt *rowners,*dlens,*olens,i,rstart,rend,j,jj,nz = 0,*gmataj,cnt,row,*ld,bses[2];
263: Mat mat;
264: Mat_SeqAIJ *gmata;
265: PetscMPIInt tag;
266: MPI_Status status;
267: PetscBool aij;
268: MatScalar *gmataa,*ao,*ad,*gmataarestore=0;
271: MPI_Comm_rank(comm,&rank);
272: MPI_Comm_size(comm,&size);
273: if (!rank) {
274: PetscObjectTypeCompare((PetscObject)gmat,MATSEQAIJ,&aij);
275: if (!aij) SETERRQ1(PetscObjectComm((PetscObject)gmat),PETSC_ERR_SUP,"Currently no support for input matrix of type %s\n",((PetscObject)gmat)->type_name);
276: }
277: if (reuse == MAT_INITIAL_MATRIX) {
278: MatCreate(comm,&mat);
279: MatSetSizes(mat,m,m,PETSC_DETERMINE,PETSC_DETERMINE);
280: MatGetBlockSizes(gmat,&bses[0],&bses[1]);
281: MPI_Bcast(bses,2,MPIU_INT,0,comm);
282: MatSetBlockSizes(mat,bses[0],bses[1]);
283: MatSetType(mat,MATAIJ);
284: PetscMalloc1(size+1,&rowners);
285: PetscMalloc2(m,&dlens,m,&olens);
286: MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);
288: rowners[0] = 0;
289: for (i=2; i<=size; i++) rowners[i] += rowners[i-1];
290: rstart = rowners[rank];
291: rend = rowners[rank+1];
292: PetscObjectGetNewTag((PetscObject)mat,&tag);
293: if (!rank) {
294: gmata = (Mat_SeqAIJ*) gmat->data;
295: /* send row lengths to all processors */
296: for (i=0; i<m; i++) dlens[i] = gmata->ilen[i];
297: for (i=1; i<size; i++) {
298: MPI_Send(gmata->ilen + rowners[i],rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);
299: }
300: /* determine number diagonal and off-diagonal counts */
301: PetscArrayzero(olens,m);
302: PetscCalloc1(m,&ld);
303: jj = 0;
304: for (i=0; i<m; i++) {
305: for (j=0; j<dlens[i]; j++) {
306: if (gmata->j[jj] < rstart) ld[i]++;
307: if (gmata->j[jj] < rstart || gmata->j[jj] >= rend) olens[i]++;
308: jj++;
309: }
310: }
311: /* send column indices to other processes */
312: for (i=1; i<size; i++) {
313: nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]];
314: MPI_Send(&nz,1,MPIU_INT,i,tag,comm);
315: MPI_Send(gmata->j + gmata->i[rowners[i]],nz,MPIU_INT,i,tag,comm);
316: }
318: /* send numerical values to other processes */
319: for (i=1; i<size; i++) {
320: nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]];
321: MPI_Send(gmata->a + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);
322: }
323: gmataa = gmata->a;
324: gmataj = gmata->j;
326: } else {
327: /* receive row lengths */
328: MPI_Recv(dlens,m,MPIU_INT,0,tag,comm,&status);
329: /* receive column indices */
330: MPI_Recv(&nz,1,MPIU_INT,0,tag,comm,&status);
331: PetscMalloc2(nz,&gmataa,nz,&gmataj);
332: MPI_Recv(gmataj,nz,MPIU_INT,0,tag,comm,&status);
333: /* determine number diagonal and off-diagonal counts */
334: PetscArrayzero(olens,m);
335: PetscCalloc1(m,&ld);
336: jj = 0;
337: for (i=0; i<m; i++) {
338: for (j=0; j<dlens[i]; j++) {
339: if (gmataj[jj] < rstart) ld[i]++;
340: if (gmataj[jj] < rstart || gmataj[jj] >= rend) olens[i]++;
341: jj++;
342: }
343: }
344: /* receive numerical values */
345: PetscArrayzero(gmataa,nz);
346: MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);
347: }
348: /* set preallocation */
349: for (i=0; i<m; i++) {
350: dlens[i] -= olens[i];
351: }
352: MatSeqAIJSetPreallocation(mat,0,dlens);
353: MatMPIAIJSetPreallocation(mat,0,dlens,0,olens);
355: for (i=0; i<m; i++) {
356: dlens[i] += olens[i];
357: }
358: cnt = 0;
359: for (i=0; i<m; i++) {
360: row = rstart + i;
361: MatSetValues(mat,1,&row,dlens[i],gmataj+cnt,gmataa+cnt,INSERT_VALUES);
362: cnt += dlens[i];
363: }
364: if (rank) {
365: PetscFree2(gmataa,gmataj);
366: }
367: PetscFree2(dlens,olens);
368: PetscFree(rowners);
370: ((Mat_MPIAIJ*)(mat->data))->ld = ld;
372: *inmat = mat;
373: } else { /* column indices are already set; only need to move over numerical values from process 0 */
374: Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->A->data;
375: Mat_SeqAIJ *Ao = (Mat_SeqAIJ*)((Mat_MPIAIJ*)((*inmat)->data))->B->data;
376: mat = *inmat;
377: PetscObjectGetNewTag((PetscObject)mat,&tag);
378: if (!rank) {
379: /* send numerical values to other processes */
380: gmata = (Mat_SeqAIJ*) gmat->data;
381: MatGetOwnershipRanges(mat,(const PetscInt**)&rowners);
382: gmataa = gmata->a;
383: for (i=1; i<size; i++) {
384: nz = gmata->i[rowners[i+1]]-gmata->i[rowners[i]];
385: MPI_Send(gmataa + gmata->i[rowners[i]],nz,MPIU_SCALAR,i,tag,comm);
386: }
387: nz = gmata->i[rowners[1]]-gmata->i[rowners[0]];
388: } else {
389: /* receive numerical values from process 0*/
390: nz = Ad->nz + Ao->nz;
391: PetscMalloc1(nz,&gmataa); gmataarestore = gmataa;
392: MPI_Recv(gmataa,nz,MPIU_SCALAR,0,tag,comm,&status);
393: }
394: /* transfer numerical values into the diagonal A and off diagonal B parts of mat */
395: ld = ((Mat_MPIAIJ*)(mat->data))->ld;
396: ad = Ad->a;
397: ao = Ao->a;
398: if (mat->rmap->n) {
399: i = 0;
400: nz = ld[i]; PetscArraycpy(ao,gmataa,nz); ao += nz; gmataa += nz;
401: nz = Ad->i[i+1] - Ad->i[i]; PetscArraycpy(ad,gmataa,nz); ad += nz; gmataa += nz;
402: }
403: for (i=1; i<mat->rmap->n; i++) {
404: nz = Ao->i[i] - Ao->i[i-1] - ld[i-1] + ld[i]; PetscArraycpy(ao,gmataa,nz); ao += nz; gmataa += nz;
405: nz = Ad->i[i+1] - Ad->i[i]; PetscArraycpy(ad,gmataa,nz); ad += nz; gmataa += nz;
406: }
407: i--;
408: if (mat->rmap->n) {
409: nz = Ao->i[i+1] - Ao->i[i] - ld[i]; PetscArraycpy(ao,gmataa,nz);
410: }
411: if (rank) {
412: PetscFree(gmataarestore);
413: }
414: }
415: MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);
416: MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);
417: return(0);
418: }
420: /*
421: Local utility routine that creates a mapping from the global column
422: number to the local number in the off-diagonal part of the local
423: storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at
424: a slightly higher hash table cost; without it it is not scalable (each processor
425: has an order N integer array but is fast to acess.
426: */
427: PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat mat)
428: {
429: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
431: PetscInt n = aij->B->cmap->n,i;
434: if (!aij->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPIAIJ Matrix was assembled but is missing garray");
435: #if defined(PETSC_USE_CTABLE)
436: PetscTableCreate(n,mat->cmap->N+1,&aij->colmap);
437: for (i=0; i<n; i++) {
438: PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1,INSERT_VALUES);
439: }
440: #else
441: PetscCalloc1(mat->cmap->N+1,&aij->colmap);
442: PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N+1)*sizeof(PetscInt));
443: for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1;
444: #endif
445: return(0);
446: }
448: #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv,orow,ocol) \
449: { \
450: if (col <= lastcol1) low1 = 0; \
451: else high1 = nrow1; \
452: lastcol1 = col;\
453: while (high1-low1 > 5) { \
454: t = (low1+high1)/2; \
455: if (rp1[t] > col) high1 = t; \
456: else low1 = t; \
457: } \
458: for (_i=low1; _i<high1; _i++) { \
459: if (rp1[_i] > col) break; \
460: if (rp1[_i] == col) { \
461: if (addv == ADD_VALUES) { \
462: ap1[_i] += value; \
463: /* Not sure LogFlops will slow dow the code or not */ \
464: (void)PetscLogFlops(1.0); \
465: } \
466: else ap1[_i] = value; \
467: goto a_noinsert; \
468: } \
469: } \
470: if (value == 0.0 && ignorezeroentries && row != col) {low1 = 0; high1 = nrow1;goto a_noinsert;} \
471: if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \
472: 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); \
473: MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \
474: N = nrow1++ - 1; a->nz++; high1++; \
475: /* shift up all the later entries in this row */ \
476: PetscArraymove(rp1+_i+1,rp1+_i,N-_i+1);\
477: PetscArraymove(ap1+_i+1,ap1+_i,N-_i+1);\
478: rp1[_i] = col; \
479: ap1[_i] = value; \
480: A->nonzerostate++;\
481: a_noinsert: ; \
482: ailen[row] = nrow1; \
483: }
485: #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv,orow,ocol) \
486: { \
487: if (col <= lastcol2) low2 = 0; \
488: else high2 = nrow2; \
489: lastcol2 = col; \
490: while (high2-low2 > 5) { \
491: t = (low2+high2)/2; \
492: if (rp2[t] > col) high2 = t; \
493: else low2 = t; \
494: } \
495: for (_i=low2; _i<high2; _i++) { \
496: if (rp2[_i] > col) break; \
497: if (rp2[_i] == col) { \
498: if (addv == ADD_VALUES) { \
499: ap2[_i] += value; \
500: (void)PetscLogFlops(1.0); \
501: } \
502: else ap2[_i] = value; \
503: goto b_noinsert; \
504: } \
505: } \
506: if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \
507: if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \
508: 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); \
509: MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \
510: N = nrow2++ - 1; b->nz++; high2++; \
511: /* shift up all the later entries in this row */ \
512: PetscArraymove(rp2+_i+1,rp2+_i,N-_i+1);\
513: PetscArraymove(ap2+_i+1,ap2+_i,N-_i+1);\
514: rp2[_i] = col; \
515: ap2[_i] = value; \
516: B->nonzerostate++; \
517: b_noinsert: ; \
518: bilen[row] = nrow2; \
519: }
521: PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[])
522: {
523: Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data;
524: Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data;
526: PetscInt l,*garray = mat->garray,diag;
529: /* code only works for square matrices A */
531: /* find size of row to the left of the diagonal part */
532: MatGetOwnershipRange(A,&diag,0);
533: row = row - diag;
534: for (l=0; l<b->i[row+1]-b->i[row]; l++) {
535: if (garray[b->j[b->i[row]+l]] > diag) break;
536: }
537: PetscArraycpy(b->a+b->i[row],v,l);
539: /* diagonal part */
540: PetscArraycpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row]));
542: /* right of diagonal part */
543: PetscArraycpy(b->a+b->i[row]+l,v+l+a->i[row+1]-a->i[row],b->i[row+1]-b->i[row]-l);
544: return(0);
545: }
547: PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
548: {
549: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
550: PetscScalar value = 0.0;
552: PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend;
553: PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col;
554: PetscBool roworiented = aij->roworiented;
556: /* Some Variables required in the macro */
557: Mat A = aij->A;
558: Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data;
559: PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j;
560: MatScalar *aa = a->a;
561: PetscBool ignorezeroentries = a->ignorezeroentries;
562: Mat B = aij->B;
563: Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data;
564: PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n;
565: MatScalar *ba = b->a;
567: PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2;
568: PetscInt nonew;
569: MatScalar *ap1,*ap2;
572: for (i=0; i<m; i++) {
573: if (im[i] < 0) continue;
574: #if defined(PETSC_USE_DEBUG)
575: 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);
576: #endif
577: if (im[i] >= rstart && im[i] < rend) {
578: row = im[i] - rstart;
579: lastcol1 = -1;
580: rp1 = aj + ai[row];
581: ap1 = aa + ai[row];
582: rmax1 = aimax[row];
583: nrow1 = ailen[row];
584: low1 = 0;
585: high1 = nrow1;
586: lastcol2 = -1;
587: rp2 = bj + bi[row];
588: ap2 = ba + bi[row];
589: rmax2 = bimax[row];
590: nrow2 = bilen[row];
591: low2 = 0;
592: high2 = nrow2;
594: for (j=0; j<n; j++) {
595: if (v) value = roworiented ? v[i*n+j] : v[i+j*m];
596: if (in[j] >= cstart && in[j] < cend) {
597: col = in[j] - cstart;
598: nonew = a->nonew;
599: if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue;
600: MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]);
601: } else if (in[j] < 0) continue;
602: #if defined(PETSC_USE_DEBUG)
603: 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);
604: #endif
605: else {
606: if (mat->was_assembled) {
607: if (!aij->colmap) {
608: MatCreateColmap_MPIAIJ_Private(mat);
609: }
610: #if defined(PETSC_USE_CTABLE)
611: PetscTableFind(aij->colmap,in[j]+1,&col);
612: col--;
613: #else
614: col = aij->colmap[in[j]] - 1;
615: #endif
616: if (col < 0 && !((Mat_SeqAIJ*)(aij->B->data))->nonew) {
617: MatDisAssemble_MPIAIJ(mat);
618: col = in[j];
619: /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */
620: B = aij->B;
621: b = (Mat_SeqAIJ*)B->data;
622: bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j; ba = b->a;
623: rp2 = bj + bi[row];
624: ap2 = ba + bi[row];
625: rmax2 = bimax[row];
626: nrow2 = bilen[row];
627: low2 = 0;
628: high2 = nrow2;
629: bm = aij->B->rmap->n;
630: ba = b->a;
631: } else if (col < 0) {
632: if (1 == ((Mat_SeqAIJ*)(aij->B->data))->nonew) {
633: PetscInfo3(mat,"Skipping of insertion of new nonzero location in off-diagonal portion of matrix %g(%D,%D)\n",(double)PetscRealPart(value),im[i],in[j]);
634: } else SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", im[i], in[j]);
635: }
636: } else col = in[j];
637: nonew = b->nonew;
638: MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]);
639: }
640: }
641: } else {
642: 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]);
643: if (!aij->donotstash) {
644: mat->assembled = PETSC_FALSE;
645: if (roworiented) {
646: MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
647: } else {
648: MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
649: }
650: }
651: }
652: }
653: return(0);
654: }
656: /*
657: This function sets the j and ilen arrays (of the diagonal and off-diagonal part) of an MPIAIJ-matrix.
658: The values in mat_i have to be sorted and the values in mat_j have to be sorted for each row (CSR-like).
659: No off-processor parts off the matrix are allowed here and mat->was_assembled has to be PETSC_FALSE.
660: */
661: PetscErrorCode MatSetValues_MPIAIJ_CopyFromCSRFormat_Symbolic(Mat mat,const PetscInt mat_j[],const PetscInt mat_i[])
662: {
663: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
664: Mat A = aij->A; /* diagonal part of the matrix */
665: Mat B = aij->B; /* offdiagonal part of the matrix */
666: Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data;
667: Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data;
668: PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,col;
669: PetscInt *ailen = a->ilen,*aj = a->j;
670: PetscInt *bilen = b->ilen,*bj = b->j;
671: PetscInt am = aij->A->rmap->n,j;
672: PetscInt diag_so_far = 0,dnz;
673: PetscInt offd_so_far = 0,onz;
676: /* Iterate over all rows of the matrix */
677: for (j=0; j<am; j++) {
678: dnz = onz = 0;
679: /* Iterate over all non-zero columns of the current row */
680: for (col=mat_i[j]; col<mat_i[j+1]; col++) {
681: /* If column is in the diagonal */
682: if (mat_j[col] >= cstart && mat_j[col] < cend) {
683: aj[diag_so_far++] = mat_j[col] - cstart;
684: dnz++;
685: } else { /* off-diagonal entries */
686: bj[offd_so_far++] = mat_j[col];
687: onz++;
688: }
689: }
690: ailen[j] = dnz;
691: bilen[j] = onz;
692: }
693: return(0);
694: }
696: /*
697: This function sets the local j, a and ilen arrays (of the diagonal and off-diagonal part) of an MPIAIJ-matrix.
698: The values in mat_i have to be sorted and the values in mat_j have to be sorted for each row (CSR-like).
699: No off-processor parts off the matrix are allowed here, they are set at a later point by MatSetValues_MPIAIJ.
700: Also, mat->was_assembled has to be false, otherwise the statement aj[rowstart_diag+dnz_row] = mat_j[col] - cstart;
701: would not be true and the more complex MatSetValues_MPIAIJ has to be used.
702: */
703: PetscErrorCode MatSetValues_MPIAIJ_CopyFromCSRFormat(Mat mat,const PetscInt mat_j[],const PetscInt mat_i[],const PetscScalar mat_a[])
704: {
705: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
706: Mat A = aij->A; /* diagonal part of the matrix */
707: Mat B = aij->B; /* offdiagonal part of the matrix */
708: Mat_SeqAIJ *aijd =(Mat_SeqAIJ*)(aij->A)->data,*aijo=(Mat_SeqAIJ*)(aij->B)->data;
709: Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data;
710: Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data;
711: PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend;
712: PetscInt *ailen = a->ilen,*aj = a->j;
713: PetscInt *bilen = b->ilen,*bj = b->j;
714: PetscInt am = aij->A->rmap->n,j;
715: PetscInt *full_diag_i=aijd->i,*full_offd_i=aijo->i; /* These variables can also include non-local elements, which are set at a later point. */
716: PetscInt col,dnz_row,onz_row,rowstart_diag,rowstart_offd;
717: PetscScalar *aa = a->a,*ba = b->a;
720: /* Iterate over all rows of the matrix */
721: for (j=0; j<am; j++) {
722: dnz_row = onz_row = 0;
723: rowstart_offd = full_offd_i[j];
724: rowstart_diag = full_diag_i[j];
725: /* Iterate over all non-zero columns of the current row */
726: for (col=mat_i[j]; col<mat_i[j+1]; col++) {
727: /* If column is in the diagonal */
728: if (mat_j[col] >= cstart && mat_j[col] < cend) {
729: aj[rowstart_diag+dnz_row] = mat_j[col] - cstart;
730: aa[rowstart_diag+dnz_row] = mat_a[col];
731: dnz_row++;
732: } else { /* off-diagonal entries */
733: bj[rowstart_offd+onz_row] = mat_j[col];
734: ba[rowstart_offd+onz_row] = mat_a[col];
735: onz_row++;
736: }
737: }
738: ailen[j] = dnz_row;
739: bilen[j] = onz_row;
740: }
741: return(0);
742: }
744: PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
745: {
746: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
748: PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend;
749: PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col;
752: for (i=0; i<m; i++) {
753: if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/
754: 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);
755: if (idxm[i] >= rstart && idxm[i] < rend) {
756: row = idxm[i] - rstart;
757: for (j=0; j<n; j++) {
758: if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */
759: 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);
760: if (idxn[j] >= cstart && idxn[j] < cend) {
761: col = idxn[j] - cstart;
762: MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);
763: } else {
764: if (!aij->colmap) {
765: MatCreateColmap_MPIAIJ_Private(mat);
766: }
767: #if defined(PETSC_USE_CTABLE)
768: PetscTableFind(aij->colmap,idxn[j]+1,&col);
769: col--;
770: #else
771: col = aij->colmap[idxn[j]] - 1;
772: #endif
773: if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0;
774: else {
775: MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);
776: }
777: }
778: }
779: } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
780: }
781: return(0);
782: }
784: extern PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat,Vec,Vec);
786: PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode)
787: {
788: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
790: PetscInt nstash,reallocs;
793: if (aij->donotstash || mat->nooffprocentries) return(0);
795: MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
796: MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
797: PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
798: return(0);
799: }
801: PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode)
802: {
803: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
804: Mat_SeqAIJ *a = (Mat_SeqAIJ*)aij->A->data;
806: PetscMPIInt n;
807: PetscInt i,j,rstart,ncols,flg;
808: PetscInt *row,*col;
809: PetscBool other_disassembled;
810: PetscScalar *val;
812: /* do not use 'b = (Mat_SeqAIJ*)aij->B->data' as B can be reset in disassembly */
815: if (!aij->donotstash && !mat->nooffprocentries) {
816: while (1) {
817: MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);
818: if (!flg) break;
820: for (i=0; i<n; ) {
821: /* Now identify the consecutive vals belonging to the same row */
822: for (j=i,rstart=row[j]; j<n; j++) {
823: if (row[j] != rstart) break;
824: }
825: if (j < n) ncols = j-i;
826: else ncols = n-i;
827: /* Now assemble all these values with a single function call */
828: MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);
830: i = j;
831: }
832: }
833: MatStashScatterEnd_Private(&mat->stash);
834: }
835: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
836: if (mat->valid_GPU_matrix == PETSC_OFFLOAD_CPU) aij->A->valid_GPU_matrix = PETSC_OFFLOAD_CPU;
837: #endif
838: MatAssemblyBegin(aij->A,mode);
839: MatAssemblyEnd(aij->A,mode);
841: /* determine if any processor has disassembled, if so we must
842: also disassemble ourself, in order that we may reassemble. */
843: /*
844: if nonzero structure of submatrix B cannot change then we know that
845: no processor disassembled thus we can skip this stuff
846: */
847: if (!((Mat_SeqAIJ*)aij->B->data)->nonew) {
848: MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
849: if (mat->was_assembled && !other_disassembled) {
850: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
851: aij->B->valid_GPU_matrix = PETSC_OFFLOAD_BOTH; /* do not copy on the GPU when assembling inside MatDisAssemble_MPIAIJ */
852: #endif
853: MatDisAssemble_MPIAIJ(mat);
854: }
855: }
856: if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
857: MatSetUpMultiply_MPIAIJ(mat);
858: }
859: MatSetOption(aij->B,MAT_USE_INODES,PETSC_FALSE);
860: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
861: if (mat->valid_GPU_matrix == PETSC_OFFLOAD_CPU && aij->B->valid_GPU_matrix != PETSC_OFFLOAD_UNALLOCATED) aij->B->valid_GPU_matrix = PETSC_OFFLOAD_CPU;
862: #endif
863: MatAssemblyBegin(aij->B,mode);
864: MatAssemblyEnd(aij->B,mode);
866: PetscFree2(aij->rowvalues,aij->rowindices);
868: aij->rowvalues = 0;
870: VecDestroy(&aij->diag);
871: if (a->inode.size) mat->ops->multdiagonalblock = MatMultDiagonalBlock_MPIAIJ;
873: /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
874: if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqAIJ*)(aij->A->data))->nonew) {
875: PetscObjectState state = aij->A->nonzerostate + aij->B->nonzerostate;
876: MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));
877: }
878: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
879: mat->valid_GPU_matrix = PETSC_OFFLOAD_BOTH;
880: #endif
881: return(0);
882: }
884: PetscErrorCode MatZeroEntries_MPIAIJ(Mat A)
885: {
886: Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data;
890: MatZeroEntries(l->A);
891: MatZeroEntries(l->B);
892: return(0);
893: }
895: PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
896: {
897: Mat_MPIAIJ *mat = (Mat_MPIAIJ *) A->data;
898: PetscObjectState sA, sB;
899: PetscInt *lrows;
900: PetscInt r, len;
901: PetscBool cong, lch, gch;
902: PetscErrorCode ierr;
905: /* get locally owned rows */
906: MatZeroRowsMapLocal_Private(A,N,rows,&len,&lrows);
907: MatHasCongruentLayouts(A,&cong);
908: /* fix right hand side if needed */
909: if (x && b) {
910: const PetscScalar *xx;
911: PetscScalar *bb;
913: if (!cong) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Need matching row/col layout");
914: VecGetArrayRead(x, &xx);
915: VecGetArray(b, &bb);
916: for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]];
917: VecRestoreArrayRead(x, &xx);
918: VecRestoreArray(b, &bb);
919: }
921: sA = mat->A->nonzerostate;
922: sB = mat->B->nonzerostate;
924: if (diag != 0.0 && cong) {
925: MatZeroRows(mat->A, len, lrows, diag, NULL, NULL);
926: MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);
927: } else if (diag != 0.0) { /* non-square or non congruent layouts -> if keepnonzeropattern is false, we allow for new insertion */
928: Mat_SeqAIJ *aijA = (Mat_SeqAIJ*)mat->A->data;
929: Mat_SeqAIJ *aijB = (Mat_SeqAIJ*)mat->B->data;
930: PetscInt nnwA, nnwB;
931: PetscBool nnzA, nnzB;
933: nnwA = aijA->nonew;
934: nnwB = aijB->nonew;
935: nnzA = aijA->keepnonzeropattern;
936: nnzB = aijB->keepnonzeropattern;
937: if (!nnzA) {
938: PetscInfo(mat->A,"Requested to not keep the pattern and add a nonzero diagonal; may encounter reallocations on diagonal block.\n");
939: aijA->nonew = 0;
940: }
941: if (!nnzB) {
942: PetscInfo(mat->B,"Requested to not keep the pattern and add a nonzero diagonal; may encounter reallocations on off-diagonal block.\n");
943: aijB->nonew = 0;
944: }
945: /* Must zero here before the next loop */
946: MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);
947: MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);
948: for (r = 0; r < len; ++r) {
949: const PetscInt row = lrows[r] + A->rmap->rstart;
950: if (row >= A->cmap->N) continue;
951: MatSetValues(A, 1, &row, 1, &row, &diag, INSERT_VALUES);
952: }
953: aijA->nonew = nnwA;
954: aijB->nonew = nnwB;
955: } else {
956: MatZeroRows(mat->A, len, lrows, 0.0, NULL, NULL);
957: MatZeroRows(mat->B, len, lrows, 0.0, NULL, NULL);
958: }
959: PetscFree(lrows);
960: MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
961: MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
963: /* reduce nonzerostate */
964: lch = (PetscBool)(sA != mat->A->nonzerostate || sB != mat->B->nonzerostate);
965: MPIU_Allreduce(&lch,&gch,1,MPIU_BOOL,MPI_LOR,PetscObjectComm((PetscObject)A));
966: if (gch) A->nonzerostate++;
967: return(0);
968: }
970: PetscErrorCode MatZeroRowsColumns_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
971: {
972: Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data;
973: PetscErrorCode ierr;
974: PetscMPIInt n = A->rmap->n;
975: PetscInt i,j,r,m,p = 0,len = 0;
976: PetscInt *lrows,*owners = A->rmap->range;
977: PetscSFNode *rrows;
978: PetscSF sf;
979: const PetscScalar *xx;
980: PetscScalar *bb,*mask;
981: Vec xmask,lmask;
982: Mat_SeqAIJ *aij = (Mat_SeqAIJ*)l->B->data;
983: const PetscInt *aj, *ii,*ridx;
984: PetscScalar *aa;
987: /* Create SF where leaves are input rows and roots are owned rows */
988: PetscMalloc1(n, &lrows);
989: for (r = 0; r < n; ++r) lrows[r] = -1;
990: PetscMalloc1(N, &rrows);
991: for (r = 0; r < N; ++r) {
992: const PetscInt idx = rows[r];
993: 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);
994: if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */
995: PetscLayoutFindOwner(A->rmap,idx,&p);
996: }
997: rrows[r].rank = p;
998: rrows[r].index = rows[r] - owners[p];
999: }
1000: PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);
1001: PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);
1002: /* Collect flags for rows to be zeroed */
1003: PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
1004: PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);
1005: PetscSFDestroy(&sf);
1006: /* Compress and put in row numbers */
1007: for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r;
1008: /* zero diagonal part of matrix */
1009: MatZeroRowsColumns(l->A,len,lrows,diag,x,b);
1010: /* handle off diagonal part of matrix */
1011: MatCreateVecs(A,&xmask,NULL);
1012: VecDuplicate(l->lvec,&lmask);
1013: VecGetArray(xmask,&bb);
1014: for (i=0; i<len; i++) bb[lrows[i]] = 1;
1015: VecRestoreArray(xmask,&bb);
1016: VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);
1017: VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);
1018: VecDestroy(&xmask);
1019: if (x && b) { /* this code is buggy when the row and column layout don't match */
1020: PetscBool cong;
1022: MatHasCongruentLayouts(A,&cong);
1023: if (!cong) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Need matching row/col layout");
1024: VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);
1025: VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);
1026: VecGetArrayRead(l->lvec,&xx);
1027: VecGetArray(b,&bb);
1028: }
1029: VecGetArray(lmask,&mask);
1030: /* remove zeroed rows of off diagonal matrix */
1031: ii = aij->i;
1032: for (i=0; i<len; i++) {
1033: PetscArrayzero(aij->a + ii[lrows[i]],ii[lrows[i]+1] - ii[lrows[i]]);
1034: }
1035: /* loop over all elements of off process part of matrix zeroing removed columns*/
1036: if (aij->compressedrow.use) {
1037: m = aij->compressedrow.nrows;
1038: ii = aij->compressedrow.i;
1039: ridx = aij->compressedrow.rindex;
1040: for (i=0; i<m; i++) {
1041: n = ii[i+1] - ii[i];
1042: aj = aij->j + ii[i];
1043: aa = aij->a + ii[i];
1045: for (j=0; j<n; j++) {
1046: if (PetscAbsScalar(mask[*aj])) {
1047: if (b) bb[*ridx] -= *aa*xx[*aj];
1048: *aa = 0.0;
1049: }
1050: aa++;
1051: aj++;
1052: }
1053: ridx++;
1054: }
1055: } else { /* do not use compressed row format */
1056: m = l->B->rmap->n;
1057: for (i=0; i<m; i++) {
1058: n = ii[i+1] - ii[i];
1059: aj = aij->j + ii[i];
1060: aa = aij->a + ii[i];
1061: for (j=0; j<n; j++) {
1062: if (PetscAbsScalar(mask[*aj])) {
1063: if (b) bb[i] -= *aa*xx[*aj];
1064: *aa = 0.0;
1065: }
1066: aa++;
1067: aj++;
1068: }
1069: }
1070: }
1071: if (x && b) {
1072: VecRestoreArray(b,&bb);
1073: VecRestoreArrayRead(l->lvec,&xx);
1074: }
1075: VecRestoreArray(lmask,&mask);
1076: VecDestroy(&lmask);
1077: PetscFree(lrows);
1079: /* only change matrix nonzero state if pattern was allowed to be changed */
1080: if (!((Mat_SeqAIJ*)(l->A->data))->keepnonzeropattern) {
1081: PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate;
1082: MPIU_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));
1083: }
1084: return(0);
1085: }
1087: PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy)
1088: {
1089: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1091: PetscInt nt;
1092: VecScatter Mvctx = a->Mvctx;
1095: VecGetLocalSize(xx,&nt);
1096: 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);
1098: VecScatterBegin(Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1099: (*a->A->ops->mult)(a->A,xx,yy);
1100: VecScatterEnd(Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1101: (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
1102: return(0);
1103: }
1105: PetscErrorCode MatMultDiagonalBlock_MPIAIJ(Mat A,Vec bb,Vec xx)
1106: {
1107: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1111: MatMultDiagonalBlock(a->A,bb,xx);
1112: return(0);
1113: }
1115: PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1116: {
1117: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1119: VecScatter Mvctx = a->Mvctx;
1122: if (a->Mvctx_mpi1_flg) Mvctx = a->Mvctx_mpi1;
1123: VecScatterBegin(Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1124: (*a->A->ops->multadd)(a->A,xx,yy,zz);
1125: VecScatterEnd(Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1126: (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);
1127: return(0);
1128: }
1130: PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy)
1131: {
1132: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1136: /* do nondiagonal part */
1137: (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1138: /* do local part */
1139: (*a->A->ops->multtranspose)(a->A,xx,yy);
1140: /* add partial results together */
1141: VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1142: VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1143: return(0);
1144: }
1146: PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f)
1147: {
1148: MPI_Comm comm;
1149: Mat_MPIAIJ *Aij = (Mat_MPIAIJ*) Amat->data, *Bij;
1150: Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs;
1151: IS Me,Notme;
1153: PetscInt M,N,first,last,*notme,i;
1154: PetscBool lf;
1155: PetscMPIInt size;
1158: /* Easy test: symmetric diagonal block */
1159: Bij = (Mat_MPIAIJ*) Bmat->data; Bdia = Bij->A;
1160: MatIsTranspose(Adia,Bdia,tol,&lf);
1161: MPIU_Allreduce(&lf,f,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)Amat));
1162: if (!*f) return(0);
1163: PetscObjectGetComm((PetscObject)Amat,&comm);
1164: MPI_Comm_size(comm,&size);
1165: if (size == 1) return(0);
1167: /* Hard test: off-diagonal block. This takes a MatCreateSubMatrix. */
1168: MatGetSize(Amat,&M,&N);
1169: MatGetOwnershipRange(Amat,&first,&last);
1170: PetscMalloc1(N-last+first,¬me);
1171: for (i=0; i<first; i++) notme[i] = i;
1172: for (i=last; i<M; i++) notme[i-last+first] = i;
1173: ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);
1174: ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);
1175: MatCreateSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);
1176: Aoff = Aoffs[0];
1177: MatCreateSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);
1178: Boff = Boffs[0];
1179: MatIsTranspose(Aoff,Boff,tol,f);
1180: MatDestroyMatrices(1,&Aoffs);
1181: MatDestroyMatrices(1,&Boffs);
1182: ISDestroy(&Me);
1183: ISDestroy(&Notme);
1184: PetscFree(notme);
1185: return(0);
1186: }
1188: PetscErrorCode MatIsSymmetric_MPIAIJ(Mat A,PetscReal tol,PetscBool *f)
1189: {
1193: MatIsTranspose_MPIAIJ(A,A,tol,f);
1194: return(0);
1195: }
1197: PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1198: {
1199: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1203: /* do nondiagonal part */
1204: (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1205: /* do local part */
1206: (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);
1207: /* add partial results together */
1208: VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1209: VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1210: return(0);
1211: }
1213: /*
1214: This only works correctly for square matrices where the subblock A->A is the
1215: diagonal block
1216: */
1217: PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v)
1218: {
1220: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1223: if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block");
1224: 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");
1225: MatGetDiagonal(a->A,v);
1226: return(0);
1227: }
1229: PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa)
1230: {
1231: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1235: MatScale(a->A,aa);
1236: MatScale(a->B,aa);
1237: return(0);
1238: }
1240: PetscErrorCode MatDestroy_MPIAIJ(Mat mat)
1241: {
1242: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
1246: #if defined(PETSC_USE_LOG)
1247: PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N);
1248: #endif
1249: MatStashDestroy_Private(&mat->stash);
1250: VecDestroy(&aij->diag);
1251: MatDestroy(&aij->A);
1252: MatDestroy(&aij->B);
1253: #if defined(PETSC_USE_CTABLE)
1254: PetscTableDestroy(&aij->colmap);
1255: #else
1256: PetscFree(aij->colmap);
1257: #endif
1258: PetscFree(aij->garray);
1259: VecDestroy(&aij->lvec);
1260: VecScatterDestroy(&aij->Mvctx);
1261: if (aij->Mvctx_mpi1) {VecScatterDestroy(&aij->Mvctx_mpi1);}
1262: PetscFree2(aij->rowvalues,aij->rowindices);
1263: PetscFree(aij->ld);
1264: PetscFree(mat->data);
1266: PetscObjectChangeTypeName((PetscObject)mat,0);
1267: PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
1268: PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
1269: PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);
1270: PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C",NULL);
1271: PetscObjectComposeFunction((PetscObject)mat,"MatResetPreallocation_C",NULL);
1272: PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C",NULL);
1273: PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);
1274: PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_mpisbaij_C",NULL);
1275: #if defined(PETSC_HAVE_ELEMENTAL)
1276: PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_elemental_C",NULL);
1277: #endif
1278: #if defined(PETSC_HAVE_HYPRE)
1279: PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_hypre_C",NULL);
1280: PetscObjectComposeFunction((PetscObject)mat,"MatMatMatMult_transpose_mpiaij_mpiaij_C",NULL);
1281: #endif
1282: PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpiaij_is_C",NULL);
1283: PetscObjectComposeFunction((PetscObject)mat,"MatPtAP_is_mpiaij_C",NULL);
1284: return(0);
1285: }
1287: PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer)
1288: {
1289: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
1290: Mat_SeqAIJ *A = (Mat_SeqAIJ*)aij->A->data;
1291: Mat_SeqAIJ *B = (Mat_SeqAIJ*)aij->B->data;
1293: PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag;
1294: int fd;
1295: PetscInt nz,header[4],*row_lengths,*range=0,rlen,i;
1296: PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap->rstart,rnz = 0;
1297: PetscScalar *column_values;
1298: PetscInt message_count,flowcontrolcount;
1299: FILE *file;
1302: MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
1303: MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);
1304: nz = A->nz + B->nz;
1305: PetscViewerBinaryGetDescriptor(viewer,&fd);
1306: if (!rank) {
1307: header[0] = MAT_FILE_CLASSID;
1308: header[1] = mat->rmap->N;
1309: header[2] = mat->cmap->N;
1311: MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
1312: PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);
1313: /* get largest number of rows any processor has */
1314: rlen = mat->rmap->n;
1315: range = mat->rmap->range;
1316: for (i=1; i<size; i++) rlen = PetscMax(rlen,range[i+1] - range[i]);
1317: } else {
1318: MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
1319: rlen = mat->rmap->n;
1320: }
1322: /* load up the local row counts */
1323: PetscMalloc1(rlen+1,&row_lengths);
1324: 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];
1326: /* store the row lengths to the file */
1327: PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1328: if (!rank) {
1329: PetscBinaryWrite(fd,row_lengths,mat->rmap->n,PETSC_INT,PETSC_TRUE);
1330: for (i=1; i<size; i++) {
1331: PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1332: rlen = range[i+1] - range[i];
1333: MPIULong_Recv(row_lengths,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));
1334: PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);
1335: }
1336: PetscViewerFlowControlEndMaster(viewer,&message_count);
1337: } else {
1338: PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1339: MPIULong_Send(row_lengths,mat->rmap->n,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1340: PetscViewerFlowControlEndWorker(viewer,&message_count);
1341: }
1342: PetscFree(row_lengths);
1344: /* load up the local column indices */
1345: nzmax = nz; /* th processor needs space a largest processor needs */
1346: MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));
1347: PetscMalloc1(nzmax+1,&column_indices);
1348: cnt = 0;
1349: for (i=0; i<mat->rmap->n; i++) {
1350: for (j=B->i[i]; j<B->i[i+1]; j++) {
1351: if ((col = garray[B->j[j]]) > cstart) break;
1352: column_indices[cnt++] = col;
1353: }
1354: for (k=A->i[i]; k<A->i[i+1]; k++) column_indices[cnt++] = A->j[k] + cstart;
1355: for (; j<B->i[i+1]; j++) column_indices[cnt++] = garray[B->j[j]];
1356: }
1357: 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);
1359: /* store the column indices to the file */
1360: PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1361: if (!rank) {
1362: MPI_Status status;
1363: PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);
1364: for (i=1; i<size; i++) {
1365: PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1366: MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1367: if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax);
1368: MPIULong_Recv(column_indices,rnz,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat));
1369: PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);
1370: }
1371: PetscViewerFlowControlEndMaster(viewer,&message_count);
1372: } else {
1373: PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1374: MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1375: MPIULong_Send(column_indices,nz,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1376: PetscViewerFlowControlEndWorker(viewer,&message_count);
1377: }
1378: PetscFree(column_indices);
1380: /* load up the local column values */
1381: PetscMalloc1(nzmax+1,&column_values);
1382: cnt = 0;
1383: for (i=0; i<mat->rmap->n; i++) {
1384: for (j=B->i[i]; j<B->i[i+1]; j++) {
1385: if (garray[B->j[j]] > cstart) break;
1386: column_values[cnt++] = B->a[j];
1387: }
1388: for (k=A->i[i]; k<A->i[i+1]; k++) column_values[cnt++] = A->a[k];
1389: for (; j<B->i[i+1]; j++) column_values[cnt++] = B->a[j];
1390: }
1391: 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);
1393: /* store the column values to the file */
1394: PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1395: if (!rank) {
1396: MPI_Status status;
1397: PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);
1398: for (i=1; i<size; i++) {
1399: PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1400: MPI_Recv(&rnz,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1401: if (rnz > nzmax) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax);
1402: MPIULong_Recv(column_values,rnz,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat));
1403: PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);
1404: }
1405: PetscViewerFlowControlEndMaster(viewer,&message_count);
1406: } else {
1407: PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1408: MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1409: MPIULong_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));
1410: PetscViewerFlowControlEndWorker(viewer,&message_count);
1411: }
1412: PetscFree(column_values);
1414: PetscViewerBinaryGetInfoPointer(viewer,&file);
1415: if (file) fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(mat->rmap->bs));
1416: return(0);
1417: }
1419: #include <petscdraw.h>
1420: PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
1421: {
1422: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
1423: PetscErrorCode ierr;
1424: PetscMPIInt rank = aij->rank,size = aij->size;
1425: PetscBool isdraw,iascii,isbinary;
1426: PetscViewer sviewer;
1427: PetscViewerFormat format;
1430: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1431: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1432: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1433: if (iascii) {
1434: PetscViewerGetFormat(viewer,&format);
1435: if (format == PETSC_VIEWER_LOAD_BALANCE) {
1436: PetscInt i,nmax = 0,nmin = PETSC_MAX_INT,navg = 0,*nz,nzlocal = ((Mat_SeqAIJ*) (aij->A->data))->nz + ((Mat_SeqAIJ*) (aij->B->data))->nz;
1437: PetscMalloc1(size,&nz);
1438: MPI_Allgather(&nzlocal,1,MPIU_INT,nz,1,MPIU_INT,PetscObjectComm((PetscObject)mat));
1439: for (i=0; i<(PetscInt)size; i++) {
1440: nmax = PetscMax(nmax,nz[i]);
1441: nmin = PetscMin(nmin,nz[i]);
1442: navg += nz[i];
1443: }
1444: PetscFree(nz);
1445: navg = navg/size;
1446: PetscViewerASCIIPrintf(viewer,"Load Balance - Nonzeros: Min %D avg %D max %D\n",nmin,navg,nmax);
1447: return(0);
1448: }
1449: PetscViewerGetFormat(viewer,&format);
1450: if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
1451: MatInfo info;
1452: PetscBool inodes;
1454: MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
1455: MatGetInfo(mat,MAT_LOCAL,&info);
1456: MatInodeGetInodeSizes(aij->A,NULL,(PetscInt**)&inodes,NULL);
1457: PetscViewerASCIIPushSynchronized(viewer);
1458: if (!inodes) {
1459: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %g, not using I-node routines\n",
1460: rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(double)info.memory);
1461: } else {
1462: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %g, using I-node routines\n",
1463: rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(double)info.memory);
1464: }
1465: MatGetInfo(aij->A,MAT_LOCAL,&info);
1466: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
1467: MatGetInfo(aij->B,MAT_LOCAL,&info);
1468: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
1469: PetscViewerFlush(viewer);
1470: PetscViewerASCIIPopSynchronized(viewer);
1471: PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
1472: VecScatterView(aij->Mvctx,viewer);
1473: return(0);
1474: } else if (format == PETSC_VIEWER_ASCII_INFO) {
1475: PetscInt inodecount,inodelimit,*inodes;
1476: MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);
1477: if (inodes) {
1478: PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);
1479: } else {
1480: PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");
1481: }
1482: return(0);
1483: } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
1484: return(0);
1485: }
1486: } else if (isbinary) {
1487: if (size == 1) {
1488: PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);
1489: MatView(aij->A,viewer);
1490: } else {
1491: MatView_MPIAIJ_Binary(mat,viewer);
1492: }
1493: return(0);
1494: } else if (iascii && size == 1) {
1495: PetscObjectSetName((PetscObject)aij->A,((PetscObject)mat)->name);
1496: MatView(aij->A,viewer);
1497: return(0);
1498: } else if (isdraw) {
1499: PetscDraw draw;
1500: PetscBool isnull;
1501: PetscViewerDrawGetDraw(viewer,0,&draw);
1502: PetscDrawIsNull(draw,&isnull);
1503: if (isnull) return(0);
1504: }
1506: { /* assemble the entire matrix onto first processor */
1507: Mat A = NULL, Av;
1508: IS isrow,iscol;
1510: ISCreateStride(PetscObjectComm((PetscObject)mat),!rank ? mat->rmap->N : 0,0,1,&isrow);
1511: ISCreateStride(PetscObjectComm((PetscObject)mat),!rank ? mat->cmap->N : 0,0,1,&iscol);
1512: MatCreateSubMatrix(mat,isrow,iscol,MAT_INITIAL_MATRIX,&A);
1513: MatMPIAIJGetSeqAIJ(A,&Av,NULL,NULL);
1514: /* The commented code uses MatCreateSubMatrices instead */
1515: /*
1516: Mat *AA, A = NULL, Av;
1517: IS isrow,iscol;
1519: ISCreateStride(PetscObjectComm((PetscObject)mat),!rank ? mat->rmap->N : 0,0,1,&isrow);
1520: ISCreateStride(PetscObjectComm((PetscObject)mat),!rank ? mat->cmap->N : 0,0,1,&iscol);
1521: MatCreateSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&AA);
1522: if (!rank) {
1523: PetscObjectReference((PetscObject)AA[0]);
1524: A = AA[0];
1525: Av = AA[0];
1526: }
1527: MatDestroySubMatrices(1,&AA);
1528: */
1529: ISDestroy(&iscol);
1530: ISDestroy(&isrow);
1531: /*
1532: Everyone has to call to draw the matrix since the graphics waits are
1533: synchronized across all processors that share the PetscDraw object
1534: */
1535: PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
1536: if (!rank) {
1537: if (((PetscObject)mat)->name) {
1538: PetscObjectSetName((PetscObject)Av,((PetscObject)mat)->name);
1539: }
1540: MatView_SeqAIJ(Av,sviewer);
1541: }
1542: PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
1543: PetscViewerFlush(viewer);
1544: MatDestroy(&A);
1545: }
1546: return(0);
1547: }
1549: PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer)
1550: {
1552: PetscBool iascii,isdraw,issocket,isbinary;
1555: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1556: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1557: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1558: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
1559: if (iascii || isdraw || isbinary || issocket) {
1560: MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);
1561: }
1562: return(0);
1563: }
1565: PetscErrorCode MatSOR_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
1566: {
1567: Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data;
1569: Vec bb1 = 0;
1570: PetscBool hasop;
1573: if (flag == SOR_APPLY_UPPER) {
1574: (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1575: return(0);
1576: }
1578: if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) {
1579: VecDuplicate(bb,&bb1);
1580: }
1582: if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
1583: if (flag & SOR_ZERO_INITIAL_GUESS) {
1584: (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1585: its--;
1586: }
1588: while (its--) {
1589: VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1590: VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1592: /* update rhs: bb1 = bb - B*x */
1593: VecScale(mat->lvec,-1.0);
1594: (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);
1596: /* local sweep */
1597: (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);
1598: }
1599: } else if (flag & SOR_LOCAL_FORWARD_SWEEP) {
1600: if (flag & SOR_ZERO_INITIAL_GUESS) {
1601: (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1602: its--;
1603: }
1604: while (its--) {
1605: VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1606: VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1608: /* update rhs: bb1 = bb - B*x */
1609: VecScale(mat->lvec,-1.0);
1610: (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);
1612: /* local sweep */
1613: (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);
1614: }
1615: } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) {
1616: if (flag & SOR_ZERO_INITIAL_GUESS) {
1617: (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
1618: its--;
1619: }
1620: while (its--) {
1621: VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1622: VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1624: /* update rhs: bb1 = bb - B*x */
1625: VecScale(mat->lvec,-1.0);
1626: (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);
1628: /* local sweep */
1629: (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);
1630: }
1631: } else if (flag & SOR_EISENSTAT) {
1632: Vec xx1;
1634: VecDuplicate(bb,&xx1);
1635: (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);
1637: VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1638: VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1639: if (!mat->diag) {
1640: MatCreateVecs(matin,&mat->diag,NULL);
1641: MatGetDiagonal(matin,mat->diag);
1642: }
1643: MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);
1644: if (hasop) {
1645: MatMultDiagonalBlock(matin,xx,bb1);
1646: } else {
1647: VecPointwiseMult(bb1,mat->diag,xx);
1648: }
1649: VecAYPX(bb1,(omega-2.0)/omega,bb);
1651: MatMultAdd(mat->B,mat->lvec,bb1,bb1);
1653: /* local sweep */
1654: (*mat->A->ops->sor)(mat->A,bb1,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);
1655: VecAXPY(xx,1.0,xx1);
1656: VecDestroy(&xx1);
1657: } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported");
1659: VecDestroy(&bb1);
1661: matin->factorerrortype = mat->A->factorerrortype;
1662: return(0);
1663: }
1665: PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B)
1666: {
1667: Mat aA,aB,Aperm;
1668: const PetscInt *rwant,*cwant,*gcols,*ai,*bi,*aj,*bj;
1669: PetscScalar *aa,*ba;
1670: PetscInt i,j,m,n,ng,anz,bnz,*dnnz,*onnz,*tdnnz,*tonnz,*rdest,*cdest,*work,*gcdest;
1671: PetscSF rowsf,sf;
1672: IS parcolp = NULL;
1673: PetscBool done;
1677: MatGetLocalSize(A,&m,&n);
1678: ISGetIndices(rowp,&rwant);
1679: ISGetIndices(colp,&cwant);
1680: PetscMalloc3(PetscMax(m,n),&work,m,&rdest,n,&cdest);
1682: /* Invert row permutation to find out where my rows should go */
1683: PetscSFCreate(PetscObjectComm((PetscObject)A),&rowsf);
1684: PetscSFSetGraphLayout(rowsf,A->rmap,A->rmap->n,NULL,PETSC_OWN_POINTER,rwant);
1685: PetscSFSetFromOptions(rowsf);
1686: for (i=0; i<m; i++) work[i] = A->rmap->rstart + i;
1687: PetscSFReduceBegin(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);
1688: PetscSFReduceEnd(rowsf,MPIU_INT,work,rdest,MPIU_REPLACE);
1690: /* Invert column permutation to find out where my columns should go */
1691: PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
1692: PetscSFSetGraphLayout(sf,A->cmap,A->cmap->n,NULL,PETSC_OWN_POINTER,cwant);
1693: PetscSFSetFromOptions(sf);
1694: for (i=0; i<n; i++) work[i] = A->cmap->rstart + i;
1695: PetscSFReduceBegin(sf,MPIU_INT,work,cdest,MPIU_REPLACE);
1696: PetscSFReduceEnd(sf,MPIU_INT,work,cdest,MPIU_REPLACE);
1697: PetscSFDestroy(&sf);
1699: ISRestoreIndices(rowp,&rwant);
1700: ISRestoreIndices(colp,&cwant);
1701: MatMPIAIJGetSeqAIJ(A,&aA,&aB,&gcols);
1703: /* Find out where my gcols should go */
1704: MatGetSize(aB,NULL,&ng);
1705: PetscMalloc1(ng,&gcdest);
1706: PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
1707: PetscSFSetGraphLayout(sf,A->cmap,ng,NULL,PETSC_OWN_POINTER,gcols);
1708: PetscSFSetFromOptions(sf);
1709: PetscSFBcastBegin(sf,MPIU_INT,cdest,gcdest);
1710: PetscSFBcastEnd(sf,MPIU_INT,cdest,gcdest);
1711: PetscSFDestroy(&sf);
1713: PetscCalloc4(m,&dnnz,m,&onnz,m,&tdnnz,m,&tonnz);
1714: MatGetRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);
1715: MatGetRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);
1716: for (i=0; i<m; i++) {
1717: PetscInt row = rdest[i],rowner;
1718: PetscLayoutFindOwner(A->rmap,row,&rowner);
1719: for (j=ai[i]; j<ai[i+1]; j++) {
1720: PetscInt cowner,col = cdest[aj[j]];
1721: PetscLayoutFindOwner(A->cmap,col,&cowner); /* Could build an index for the columns to eliminate this search */
1722: if (rowner == cowner) dnnz[i]++;
1723: else onnz[i]++;
1724: }
1725: for (j=bi[i]; j<bi[i+1]; j++) {
1726: PetscInt cowner,col = gcdest[bj[j]];
1727: PetscLayoutFindOwner(A->cmap,col,&cowner);
1728: if (rowner == cowner) dnnz[i]++;
1729: else onnz[i]++;
1730: }
1731: }
1732: PetscSFBcastBegin(rowsf,MPIU_INT,dnnz,tdnnz);
1733: PetscSFBcastEnd(rowsf,MPIU_INT,dnnz,tdnnz);
1734: PetscSFBcastBegin(rowsf,MPIU_INT,onnz,tonnz);
1735: PetscSFBcastEnd(rowsf,MPIU_INT,onnz,tonnz);
1736: PetscSFDestroy(&rowsf);
1738: MatCreateAIJ(PetscObjectComm((PetscObject)A),A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N,0,tdnnz,0,tonnz,&Aperm);
1739: MatSeqAIJGetArray(aA,&aa);
1740: MatSeqAIJGetArray(aB,&ba);
1741: for (i=0; i<m; i++) {
1742: PetscInt *acols = dnnz,*bcols = onnz; /* Repurpose now-unneeded arrays */
1743: PetscInt j0,rowlen;
1744: rowlen = ai[i+1] - ai[i];
1745: for (j0=j=0; j<rowlen; j0=j) { /* rowlen could be larger than number of rows m, so sum in batches */
1746: for ( ; j<PetscMin(rowlen,j0+m); j++) acols[j-j0] = cdest[aj[ai[i]+j]];
1747: MatSetValues(Aperm,1,&rdest[i],j-j0,acols,aa+ai[i]+j0,INSERT_VALUES);
1748: }
1749: rowlen = bi[i+1] - bi[i];
1750: for (j0=j=0; j<rowlen; j0=j) {
1751: for ( ; j<PetscMin(rowlen,j0+m); j++) bcols[j-j0] = gcdest[bj[bi[i]+j]];
1752: MatSetValues(Aperm,1,&rdest[i],j-j0,bcols,ba+bi[i]+j0,INSERT_VALUES);
1753: }
1754: }
1755: MatAssemblyBegin(Aperm,MAT_FINAL_ASSEMBLY);
1756: MatAssemblyEnd(Aperm,MAT_FINAL_ASSEMBLY);
1757: MatRestoreRowIJ(aA,0,PETSC_FALSE,PETSC_FALSE,&anz,&ai,&aj,&done);
1758: MatRestoreRowIJ(aB,0,PETSC_FALSE,PETSC_FALSE,&bnz,&bi,&bj,&done);
1759: MatSeqAIJRestoreArray(aA,&aa);
1760: MatSeqAIJRestoreArray(aB,&ba);
1761: PetscFree4(dnnz,onnz,tdnnz,tonnz);
1762: PetscFree3(work,rdest,cdest);
1763: PetscFree(gcdest);
1764: if (parcolp) {ISDestroy(&colp);}
1765: *B = Aperm;
1766: return(0);
1767: }
1769: PetscErrorCode MatGetGhosts_MPIAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[])
1770: {
1771: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
1775: MatGetSize(aij->B,NULL,nghosts);
1776: if (ghosts) *ghosts = aij->garray;
1777: return(0);
1778: }
1780: PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info)
1781: {
1782: Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data;
1783: Mat A = mat->A,B = mat->B;
1785: PetscReal isend[5],irecv[5];
1788: info->block_size = 1.0;
1789: MatGetInfo(A,MAT_LOCAL,info);
1791: isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
1792: isend[3] = info->memory; isend[4] = info->mallocs;
1794: MatGetInfo(B,MAT_LOCAL,info);
1796: isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
1797: isend[3] += info->memory; isend[4] += info->mallocs;
1798: if (flag == MAT_LOCAL) {
1799: info->nz_used = isend[0];
1800: info->nz_allocated = isend[1];
1801: info->nz_unneeded = isend[2];
1802: info->memory = isend[3];
1803: info->mallocs = isend[4];
1804: } else if (flag == MAT_GLOBAL_MAX) {
1805: MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));
1807: info->nz_used = irecv[0];
1808: info->nz_allocated = irecv[1];
1809: info->nz_unneeded = irecv[2];
1810: info->memory = irecv[3];
1811: info->mallocs = irecv[4];
1812: } else if (flag == MAT_GLOBAL_SUM) {
1813: MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));
1815: info->nz_used = irecv[0];
1816: info->nz_allocated = irecv[1];
1817: info->nz_unneeded = irecv[2];
1818: info->memory = irecv[3];
1819: info->mallocs = irecv[4];
1820: }
1821: info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */
1822: info->fill_ratio_needed = 0;
1823: info->factor_mallocs = 0;
1824: return(0);
1825: }
1827: PetscErrorCode MatSetOption_MPIAIJ(Mat A,MatOption op,PetscBool flg)
1828: {
1829: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
1833: switch (op) {
1834: case MAT_NEW_NONZERO_LOCATIONS:
1835: case MAT_NEW_NONZERO_ALLOCATION_ERR:
1836: case MAT_UNUSED_NONZERO_LOCATION_ERR:
1837: case MAT_KEEP_NONZERO_PATTERN:
1838: case MAT_NEW_NONZERO_LOCATION_ERR:
1839: case MAT_USE_INODES:
1840: case MAT_IGNORE_ZERO_ENTRIES:
1841: MatCheckPreallocated(A,1);
1842: MatSetOption(a->A,op,flg);
1843: MatSetOption(a->B,op,flg);
1844: break;
1845: case MAT_ROW_ORIENTED:
1846: MatCheckPreallocated(A,1);
1847: a->roworiented = flg;
1849: MatSetOption(a->A,op,flg);
1850: MatSetOption(a->B,op,flg);
1851: break;
1852: case MAT_NEW_DIAGONALS:
1853: case MAT_SORTED_FULL:
1854: PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1855: break;
1856: case MAT_IGNORE_OFF_PROC_ENTRIES:
1857: a->donotstash = flg;
1858: break;
1859: /* Symmetry flags are handled directly by MatSetOption() and they don't affect preallocation */
1860: case MAT_SPD:
1861: case MAT_SYMMETRIC:
1862: case MAT_STRUCTURALLY_SYMMETRIC:
1863: case MAT_HERMITIAN:
1864: case MAT_SYMMETRY_ETERNAL:
1865: break;
1866: case MAT_SUBMAT_SINGLEIS:
1867: A->submat_singleis = flg;
1868: break;
1869: case MAT_STRUCTURE_ONLY:
1870: /* The option is handled directly by MatSetOption() */
1871: break;
1872: default:
1873: SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
1874: }
1875: return(0);
1876: }
1878: PetscErrorCode MatGetRow_MPIAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1879: {
1880: Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data;
1881: PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p;
1883: PetscInt i,*cworkA,*cworkB,**pcA,**pcB,cstart = matin->cmap->rstart;
1884: PetscInt nztot,nzA,nzB,lrow,rstart = matin->rmap->rstart,rend = matin->rmap->rend;
1885: PetscInt *cmap,*idx_p;
1888: if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active");
1889: mat->getrowactive = PETSC_TRUE;
1891: if (!mat->rowvalues && (idx || v)) {
1892: /*
1893: allocate enough space to hold information from the longest row.
1894: */
1895: Mat_SeqAIJ *Aa = (Mat_SeqAIJ*)mat->A->data,*Ba = (Mat_SeqAIJ*)mat->B->data;
1896: PetscInt max = 1,tmp;
1897: for (i=0; i<matin->rmap->n; i++) {
1898: tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i];
1899: if (max < tmp) max = tmp;
1900: }
1901: PetscMalloc2(max,&mat->rowvalues,max,&mat->rowindices);
1902: }
1904: if (row < rstart || row >= rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Only local rows");
1905: lrow = row - rstart;
1907: pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
1908: if (!v) {pvA = 0; pvB = 0;}
1909: if (!idx) {pcA = 0; if (!v) pcB = 0;}
1910: (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
1911: (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
1912: nztot = nzA + nzB;
1914: cmap = mat->garray;
1915: if (v || idx) {
1916: if (nztot) {
1917: /* Sort by increasing column numbers, assuming A and B already sorted */
1918: PetscInt imark = -1;
1919: if (v) {
1920: *v = v_p = mat->rowvalues;
1921: for (i=0; i<nzB; i++) {
1922: if (cmap[cworkB[i]] < cstart) v_p[i] = vworkB[i];
1923: else break;
1924: }
1925: imark = i;
1926: for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i];
1927: for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i];
1928: }
1929: if (idx) {
1930: *idx = idx_p = mat->rowindices;
1931: if (imark > -1) {
1932: for (i=0; i<imark; i++) {
1933: idx_p[i] = cmap[cworkB[i]];
1934: }
1935: } else {
1936: for (i=0; i<nzB; i++) {
1937: if (cmap[cworkB[i]] < cstart) idx_p[i] = cmap[cworkB[i]];
1938: else break;
1939: }
1940: imark = i;
1941: }
1942: for (i=0; i<nzA; i++) idx_p[imark+i] = cstart + cworkA[i];
1943: for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]];
1944: }
1945: } else {
1946: if (idx) *idx = 0;
1947: if (v) *v = 0;
1948: }
1949: }
1950: *nz = nztot;
1951: (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
1952: (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
1953: return(0);
1954: }
1956: PetscErrorCode MatRestoreRow_MPIAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1957: {
1958: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
1961: if (!aij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first");
1962: aij->getrowactive = PETSC_FALSE;
1963: return(0);
1964: }
1966: PetscErrorCode MatNorm_MPIAIJ(Mat mat,NormType type,PetscReal *norm)
1967: {
1968: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
1969: Mat_SeqAIJ *amat = (Mat_SeqAIJ*)aij->A->data,*bmat = (Mat_SeqAIJ*)aij->B->data;
1971: PetscInt i,j,cstart = mat->cmap->rstart;
1972: PetscReal sum = 0.0;
1973: MatScalar *v;
1976: if (aij->size == 1) {
1977: MatNorm(aij->A,type,norm);
1978: } else {
1979: if (type == NORM_FROBENIUS) {
1980: v = amat->a;
1981: for (i=0; i<amat->nz; i++) {
1982: sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
1983: }
1984: v = bmat->a;
1985: for (i=0; i<bmat->nz; i++) {
1986: sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
1987: }
1988: MPIU_Allreduce(&sum,norm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
1989: *norm = PetscSqrtReal(*norm);
1990: PetscLogFlops(2*amat->nz+2*bmat->nz);
1991: } else if (type == NORM_1) { /* max column norm */
1992: PetscReal *tmp,*tmp2;
1993: PetscInt *jj,*garray = aij->garray;
1994: PetscCalloc1(mat->cmap->N+1,&tmp);
1995: PetscMalloc1(mat->cmap->N+1,&tmp2);
1996: *norm = 0.0;
1997: v = amat->a; jj = amat->j;
1998: for (j=0; j<amat->nz; j++) {
1999: tmp[cstart + *jj++] += PetscAbsScalar(*v); v++;
2000: }
2001: v = bmat->a; jj = bmat->j;
2002: for (j=0; j<bmat->nz; j++) {
2003: tmp[garray[*jj++]] += PetscAbsScalar(*v); v++;
2004: }
2005: MPIU_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
2006: for (j=0; j<mat->cmap->N; j++) {
2007: if (tmp2[j] > *norm) *norm = tmp2[j];
2008: }
2009: PetscFree(tmp);
2010: PetscFree(tmp2);
2011: PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));
2012: } else if (type == NORM_INFINITY) { /* max row norm */
2013: PetscReal ntemp = 0.0;
2014: for (j=0; j<aij->A->rmap->n; j++) {
2015: v = amat->a + amat->i[j];
2016: sum = 0.0;
2017: for (i=0; i<amat->i[j+1]-amat->i[j]; i++) {
2018: sum += PetscAbsScalar(*v); v++;
2019: }
2020: v = bmat->a + bmat->i[j];
2021: for (i=0; i<bmat->i[j+1]-bmat->i[j]; i++) {
2022: sum += PetscAbsScalar(*v); v++;
2023: }
2024: if (sum > ntemp) ntemp = sum;
2025: }
2026: MPIU_Allreduce(&ntemp,norm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));
2027: PetscLogFlops(PetscMax(amat->nz+bmat->nz-1,0));
2028: } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for two norm");
2029: }
2030: return(0);
2031: }
2033: PetscErrorCode MatTranspose_MPIAIJ(Mat A,MatReuse reuse,Mat *matout)
2034: {
2035: Mat_MPIAIJ *a =(Mat_MPIAIJ*)A->data,*b;
2036: Mat_SeqAIJ *Aloc =(Mat_SeqAIJ*)a->A->data,*Bloc=(Mat_SeqAIJ*)a->B->data,*sub_B_diag;
2037: PetscInt M = A->rmap->N,N=A->cmap->N,ma,na,mb,nb,row,*cols,*cols_tmp,*B_diag_ilen,i,ncol,A_diag_ncol;
2038: const PetscInt *ai,*aj,*bi,*bj,*B_diag_i;
2039: PetscErrorCode ierr;
2040: Mat B,A_diag,*B_diag;
2041: const MatScalar *array;
2044: ma = A->rmap->n; na = A->cmap->n; mb = a->B->rmap->n; nb = a->B->cmap->n;
2045: ai = Aloc->i; aj = Aloc->j;
2046: bi = Bloc->i; bj = Bloc->j;
2047: if (reuse == MAT_INITIAL_MATRIX || *matout == A) {
2048: PetscInt *d_nnz,*g_nnz,*o_nnz;
2049: PetscSFNode *oloc;
2050: PETSC_UNUSED PetscSF sf;
2052: PetscMalloc4(na,&d_nnz,na,&o_nnz,nb,&g_nnz,nb,&oloc);
2053: /* compute d_nnz for preallocation */
2054: PetscArrayzero(d_nnz,na);
2055: for (i=0; i<ai[ma]; i++) {
2056: d_nnz[aj[i]]++;
2057: }
2058: /* compute local off-diagonal contributions */
2059: PetscArrayzero(g_nnz,nb);
2060: for (i=0; i<bi[ma]; i++) g_nnz[bj[i]]++;
2061: /* map those to global */
2062: PetscSFCreate(PetscObjectComm((PetscObject)A),&sf);
2063: PetscSFSetGraphLayout(sf,A->cmap,nb,NULL,PETSC_USE_POINTER,a->garray);
2064: PetscSFSetFromOptions(sf);
2065: PetscArrayzero(o_nnz,na);
2066: PetscSFReduceBegin(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);
2067: PetscSFReduceEnd(sf,MPIU_INT,g_nnz,o_nnz,MPIU_SUM);
2068: PetscSFDestroy(&sf);
2070: MatCreate(PetscObjectComm((PetscObject)A),&B);
2071: MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);
2072: MatSetBlockSizes(B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));
2073: MatSetType(B,((PetscObject)A)->type_name);
2074: MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);
2075: PetscFree4(d_nnz,o_nnz,g_nnz,oloc);
2076: } else {
2077: B = *matout;
2078: MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);
2079: }
2081: b = (Mat_MPIAIJ*)B->data;
2082: A_diag = a->A;
2083: B_diag = &b->A;
2084: sub_B_diag = (Mat_SeqAIJ*)(*B_diag)->data;
2085: A_diag_ncol = A_diag->cmap->N;
2086: B_diag_ilen = sub_B_diag->ilen;
2087: B_diag_i = sub_B_diag->i;
2089: /* Set ilen for diagonal of B */
2090: for (i=0; i<A_diag_ncol; i++) {
2091: B_diag_ilen[i] = B_diag_i[i+1] - B_diag_i[i];
2092: }
2094: /* Transpose the diagonal part of the matrix. In contrast to the offdiagonal part, this can be done
2095: very quickly (=without using MatSetValues), because all writes are local. */
2096: MatTranspose(A_diag,MAT_REUSE_MATRIX,B_diag);
2098: /* copy over the B part */
2099: PetscMalloc1(bi[mb],&cols);
2100: array = Bloc->a;
2101: row = A->rmap->rstart;
2102: for (i=0; i<bi[mb]; i++) cols[i] = a->garray[bj[i]];
2103: cols_tmp = cols;
2104: for (i=0; i<mb; i++) {
2105: ncol = bi[i+1]-bi[i];
2106: MatSetValues(B,ncol,cols_tmp,1,&row,array,INSERT_VALUES);
2107: row++;
2108: array += ncol; cols_tmp += ncol;
2109: }
2110: PetscFree(cols);
2112: MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
2113: MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
2114: if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) {
2115: *matout = B;
2116: } else {
2117: MatHeaderMerge(A,&B);
2118: }
2119: return(0);
2120: }
2122: PetscErrorCode MatDiagonalScale_MPIAIJ(Mat mat,Vec ll,Vec rr)
2123: {
2124: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
2125: Mat a = aij->A,b = aij->B;
2127: PetscInt s1,s2,s3;
2130: MatGetLocalSize(mat,&s2,&s3);
2131: if (rr) {
2132: VecGetLocalSize(rr,&s1);
2133: if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size");
2134: /* Overlap communication with computation. */
2135: VecScatterBegin(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);
2136: }
2137: if (ll) {
2138: VecGetLocalSize(ll,&s1);
2139: if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size");
2140: (*b->ops->diagonalscale)(b,ll,0);
2141: }
2142: /* scale the diagonal block */
2143: (*a->ops->diagonalscale)(a,ll,rr);
2145: if (rr) {
2146: /* Do a scatter end and then right scale the off-diagonal block */
2147: VecScatterEnd(aij->Mvctx,rr,aij->lvec,INSERT_VALUES,SCATTER_FORWARD);
2148: (*b->ops->diagonalscale)(b,0,aij->lvec);
2149: }
2150: return(0);
2151: }
2153: PetscErrorCode MatSetUnfactored_MPIAIJ(Mat A)
2154: {
2155: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2159: MatSetUnfactored(a->A);
2160: return(0);
2161: }
2163: PetscErrorCode MatEqual_MPIAIJ(Mat A,Mat B,PetscBool *flag)
2164: {
2165: Mat_MPIAIJ *matB = (Mat_MPIAIJ*)B->data,*matA = (Mat_MPIAIJ*)A->data;
2166: Mat a,b,c,d;
2167: PetscBool flg;
2171: a = matA->A; b = matA->B;
2172: c = matB->A; d = matB->B;
2174: MatEqual(a,c,&flg);
2175: if (flg) {
2176: MatEqual(b,d,&flg);
2177: }
2178: MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
2179: return(0);
2180: }
2182: PetscErrorCode MatCopy_MPIAIJ(Mat A,Mat B,MatStructure str)
2183: {
2185: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2186: Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data;
2189: /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
2190: if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
2191: /* because of the column compression in the off-processor part of the matrix a->B,
2192: the number of columns in a->B and b->B may be different, hence we cannot call
2193: the MatCopy() directly on the two parts. If need be, we can provide a more
2194: efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices
2195: then copying the submatrices */
2196: MatCopy_Basic(A,B,str);
2197: } else {
2198: MatCopy(a->A,b->A,str);
2199: MatCopy(a->B,b->B,str);
2200: }
2201: PetscObjectStateIncrease((PetscObject)B);
2202: return(0);
2203: }
2205: PetscErrorCode MatSetUp_MPIAIJ(Mat A)
2206: {
2210: MatMPIAIJSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);
2211: return(0);
2212: }
2214: /*
2215: Computes the number of nonzeros per row needed for preallocation when X and Y
2216: have different nonzero structure.
2217: */
2218: 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)
2219: {
2220: PetscInt i,j,k,nzx,nzy;
2223: /* Set the number of nonzeros in the new matrix */
2224: for (i=0; i<m; i++) {
2225: const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i];
2226: nzx = xi[i+1] - xi[i];
2227: nzy = yi[i+1] - yi[i];
2228: nnz[i] = 0;
2229: for (j=0,k=0; j<nzx; j++) { /* Point in X */
2230: for (; k<nzy && yltog[yjj[k]]<xltog[xjj[j]]; k++) nnz[i]++; /* Catch up to X */
2231: if (k<nzy && yltog[yjj[k]]==xltog[xjj[j]]) k++; /* Skip duplicate */
2232: nnz[i]++;
2233: }
2234: for (; k<nzy; k++) nnz[i]++;
2235: }
2236: return(0);
2237: }
2239: /* This is the same as MatAXPYGetPreallocation_SeqAIJ, except that the local-to-global map is provided */
2240: static PetscErrorCode MatAXPYGetPreallocation_MPIAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz)
2241: {
2243: PetscInt m = Y->rmap->N;
2244: Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data;
2245: Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data;
2248: MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);
2249: return(0);
2250: }
2252: PetscErrorCode MatAXPY_MPIAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
2253: {
2255: Mat_MPIAIJ *xx = (Mat_MPIAIJ*)X->data,*yy = (Mat_MPIAIJ*)Y->data;
2256: PetscBLASInt bnz,one=1;
2257: Mat_SeqAIJ *x,*y;
2260: if (str == SAME_NONZERO_PATTERN) {
2261: PetscScalar alpha = a;
2262: x = (Mat_SeqAIJ*)xx->A->data;
2263: PetscBLASIntCast(x->nz,&bnz);
2264: y = (Mat_SeqAIJ*)yy->A->data;
2265: PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
2266: x = (Mat_SeqAIJ*)xx->B->data;
2267: y = (Mat_SeqAIJ*)yy->B->data;
2268: PetscBLASIntCast(x->nz,&bnz);
2269: PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
2270: PetscObjectStateIncrease((PetscObject)Y);
2271: /* the MatAXPY_Basic* subroutines calls MatAssembly, so the matrix on the GPU
2272: will be updated */
2273: #if defined(PETSC_HAVE_VIENNACL) || defined(PETSC_HAVE_CUDA)
2274: if (Y->valid_GPU_matrix != PETSC_OFFLOAD_UNALLOCATED) {
2275: Y->valid_GPU_matrix = PETSC_OFFLOAD_CPU;
2276: }
2277: #endif
2278: } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
2279: MatAXPY_Basic(Y,a,X,str);
2280: } else {
2281: Mat B;
2282: PetscInt *nnz_d,*nnz_o;
2283: PetscMalloc1(yy->A->rmap->N,&nnz_d);
2284: PetscMalloc1(yy->B->rmap->N,&nnz_o);
2285: MatCreate(PetscObjectComm((PetscObject)Y),&B);
2286: PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
2287: MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
2288: MatSetBlockSizesFromMats(B,Y,Y);
2289: MatSetType(B,MATMPIAIJ);
2290: MatAXPYGetPreallocation_SeqAIJ(yy->A,xx->A,nnz_d);
2291: MatAXPYGetPreallocation_MPIAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);
2292: MatMPIAIJSetPreallocation(B,0,nnz_d,0,nnz_o);
2293: MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
2294: MatHeaderReplace(Y,&B);
2295: PetscFree(nnz_d);
2296: PetscFree(nnz_o);
2297: }
2298: return(0);
2299: }
2301: extern PetscErrorCode MatConjugate_SeqAIJ(Mat);
2303: PetscErrorCode MatConjugate_MPIAIJ(Mat mat)
2304: {
2305: #if defined(PETSC_USE_COMPLEX)
2307: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
2310: MatConjugate_SeqAIJ(aij->A);
2311: MatConjugate_SeqAIJ(aij->B);
2312: #else
2314: #endif
2315: return(0);
2316: }
2318: PetscErrorCode MatRealPart_MPIAIJ(Mat A)
2319: {
2320: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2324: MatRealPart(a->A);
2325: MatRealPart(a->B);
2326: return(0);
2327: }
2329: PetscErrorCode MatImaginaryPart_MPIAIJ(Mat A)
2330: {
2331: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2335: MatImaginaryPart(a->A);
2336: MatImaginaryPart(a->B);
2337: return(0);
2338: }
2340: PetscErrorCode MatGetRowMaxAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2341: {
2342: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2344: PetscInt i,*idxb = 0;
2345: PetscScalar *va,*vb;
2346: Vec vtmp;
2349: MatGetRowMaxAbs(a->A,v,idx);
2350: VecGetArray(v,&va);
2351: if (idx) {
2352: for (i=0; i<A->rmap->n; i++) {
2353: if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;
2354: }
2355: }
2357: VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);
2358: if (idx) {
2359: PetscMalloc1(A->rmap->n,&idxb);
2360: }
2361: MatGetRowMaxAbs(a->B,vtmp,idxb);
2362: VecGetArray(vtmp,&vb);
2364: for (i=0; i<A->rmap->n; i++) {
2365: if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) {
2366: va[i] = vb[i];
2367: if (idx) idx[i] = a->garray[idxb[i]];
2368: }
2369: }
2371: VecRestoreArray(v,&va);
2372: VecRestoreArray(vtmp,&vb);
2373: PetscFree(idxb);
2374: VecDestroy(&vtmp);
2375: return(0);
2376: }
2378: PetscErrorCode MatGetRowMinAbs_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2379: {
2380: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2382: PetscInt i,*idxb = 0;
2383: PetscScalar *va,*vb;
2384: Vec vtmp;
2387: MatGetRowMinAbs(a->A,v,idx);
2388: VecGetArray(v,&va);
2389: if (idx) {
2390: for (i=0; i<A->cmap->n; i++) {
2391: if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;
2392: }
2393: }
2395: VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);
2396: if (idx) {
2397: PetscMalloc1(A->rmap->n,&idxb);
2398: }
2399: MatGetRowMinAbs(a->B,vtmp,idxb);
2400: VecGetArray(vtmp,&vb);
2402: for (i=0; i<A->rmap->n; i++) {
2403: if (PetscAbsScalar(va[i]) > PetscAbsScalar(vb[i])) {
2404: va[i] = vb[i];
2405: if (idx) idx[i] = a->garray[idxb[i]];
2406: }
2407: }
2409: VecRestoreArray(v,&va);
2410: VecRestoreArray(vtmp,&vb);
2411: PetscFree(idxb);
2412: VecDestroy(&vtmp);
2413: return(0);
2414: }
2416: PetscErrorCode MatGetRowMin_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2417: {
2418: Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data;
2419: PetscInt n = A->rmap->n;
2420: PetscInt cstart = A->cmap->rstart;
2421: PetscInt *cmap = mat->garray;
2422: PetscInt *diagIdx, *offdiagIdx;
2423: Vec diagV, offdiagV;
2424: PetscScalar *a, *diagA, *offdiagA;
2425: PetscInt r;
2429: PetscMalloc2(n,&diagIdx,n,&offdiagIdx);
2430: VecCreateSeq(PetscObjectComm((PetscObject)A), n, &diagV);
2431: VecCreateSeq(PetscObjectComm((PetscObject)A), n, &offdiagV);
2432: MatGetRowMin(mat->A, diagV, diagIdx);
2433: MatGetRowMin(mat->B, offdiagV, offdiagIdx);
2434: VecGetArray(v, &a);
2435: VecGetArray(diagV, &diagA);
2436: VecGetArray(offdiagV, &offdiagA);
2437: for (r = 0; r < n; ++r) {
2438: if (PetscAbsScalar(diagA[r]) <= PetscAbsScalar(offdiagA[r])) {
2439: a[r] = diagA[r];
2440: idx[r] = cstart + diagIdx[r];
2441: } else {
2442: a[r] = offdiagA[r];
2443: idx[r] = cmap[offdiagIdx[r]];
2444: }
2445: }
2446: VecRestoreArray(v, &a);
2447: VecRestoreArray(diagV, &diagA);
2448: VecRestoreArray(offdiagV, &offdiagA);
2449: VecDestroy(&diagV);
2450: VecDestroy(&offdiagV);
2451: PetscFree2(diagIdx, offdiagIdx);
2452: return(0);
2453: }
2455: PetscErrorCode MatGetRowMax_MPIAIJ(Mat A, Vec v, PetscInt idx[])
2456: {
2457: Mat_MPIAIJ *mat = (Mat_MPIAIJ*) A->data;
2458: PetscInt n = A->rmap->n;
2459: PetscInt cstart = A->cmap->rstart;
2460: PetscInt *cmap = mat->garray;
2461: PetscInt *diagIdx, *offdiagIdx;
2462: Vec diagV, offdiagV;
2463: PetscScalar *a, *diagA, *offdiagA;
2464: PetscInt r;
2468: PetscMalloc2(n,&diagIdx,n,&offdiagIdx);
2469: VecCreateSeq(PETSC_COMM_SELF, n, &diagV);
2470: VecCreateSeq(PETSC_COMM_SELF, n, &offdiagV);
2471: MatGetRowMax(mat->A, diagV, diagIdx);
2472: MatGetRowMax(mat->B, offdiagV, offdiagIdx);
2473: VecGetArray(v, &a);
2474: VecGetArray(diagV, &diagA);
2475: VecGetArray(offdiagV, &offdiagA);
2476: for (r = 0; r < n; ++r) {
2477: if (PetscAbsScalar(diagA[r]) >= PetscAbsScalar(offdiagA[r])) {
2478: a[r] = diagA[r];
2479: idx[r] = cstart + diagIdx[r];
2480: } else {
2481: a[r] = offdiagA[r];
2482: idx[r] = cmap[offdiagIdx[r]];
2483: }
2484: }
2485: VecRestoreArray(v, &a);
2486: VecRestoreArray(diagV, &diagA);
2487: VecRestoreArray(offdiagV, &offdiagA);
2488: VecDestroy(&diagV);
2489: VecDestroy(&offdiagV);
2490: PetscFree2(diagIdx, offdiagIdx);
2491: return(0);
2492: }
2494: PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat mat,Mat *newmat)
2495: {
2497: Mat *dummy;
2500: MatCreateSubMatrix_MPIAIJ_All(mat,MAT_DO_NOT_GET_VALUES,MAT_INITIAL_MATRIX,&dummy);
2501: *newmat = *dummy;
2502: PetscFree(dummy);
2503: return(0);
2504: }
2506: PetscErrorCode MatInvertBlockDiagonal_MPIAIJ(Mat A,const PetscScalar **values)
2507: {
2508: Mat_MPIAIJ *a = (Mat_MPIAIJ*) A->data;
2512: MatInvertBlockDiagonal(a->A,values);
2513: A->factorerrortype = a->A->factorerrortype;
2514: return(0);
2515: }
2517: static PetscErrorCode MatSetRandom_MPIAIJ(Mat x,PetscRandom rctx)
2518: {
2520: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)x->data;
2523: if (!x->assembled && !x->preallocated) SETERRQ(PetscObjectComm((PetscObject)x), PETSC_ERR_ARG_WRONGSTATE, "MatSetRandom on an unassembled and unpreallocated MATMPIAIJ is not allowed");
2524: MatSetRandom(aij->A,rctx);
2525: if (x->assembled) {
2526: MatSetRandom(aij->B,rctx);
2527: } else {
2528: MatSetRandomSkipColumnRange_SeqAIJ_Private(aij->B,x->cmap->rstart,x->cmap->rend,rctx);
2529: }
2530: MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);
2531: MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);
2532: return(0);
2533: }
2535: PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ(Mat A,PetscBool sc)
2536: {
2538: if (sc) A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ_Scalable;
2539: else A->ops->increaseoverlap = MatIncreaseOverlap_MPIAIJ;
2540: return(0);
2541: }
2543: /*@
2544: MatMPIAIJSetUseScalableIncreaseOverlap - Determine if the matrix uses a scalable algorithm to compute the overlap
2546: Collective on Mat
2548: Input Parameters:
2549: + A - the matrix
2550: - sc - PETSC_TRUE indicates use the scalable algorithm (default is not to use the scalable algorithm)
2552: Level: advanced
2554: @*/
2555: PetscErrorCode MatMPIAIJSetUseScalableIncreaseOverlap(Mat A,PetscBool sc)
2556: {
2557: PetscErrorCode ierr;
2560: PetscTryMethod(A,"MatMPIAIJSetUseScalableIncreaseOverlap_C",(Mat,PetscBool),(A,sc));
2561: return(0);
2562: }
2564: PetscErrorCode MatSetFromOptions_MPIAIJ(PetscOptionItems *PetscOptionsObject,Mat A)
2565: {
2566: PetscErrorCode ierr;
2567: PetscBool sc = PETSC_FALSE,flg;
2570: PetscOptionsHead(PetscOptionsObject,"MPIAIJ options");
2571: if (A->ops->increaseoverlap == MatIncreaseOverlap_MPIAIJ_Scalable) sc = PETSC_TRUE;
2572: PetscOptionsBool("-mat_increase_overlap_scalable","Use a scalable algorithm to compute the overlap","MatIncreaseOverlap",sc,&sc,&flg);
2573: if (flg) {
2574: MatMPIAIJSetUseScalableIncreaseOverlap(A,sc);
2575: }
2576: PetscOptionsTail();
2577: return(0);
2578: }
2580: PetscErrorCode MatShift_MPIAIJ(Mat Y,PetscScalar a)
2581: {
2583: Mat_MPIAIJ *maij = (Mat_MPIAIJ*)Y->data;
2584: Mat_SeqAIJ *aij = (Mat_SeqAIJ*)maij->A->data;
2587: if (!Y->preallocated) {
2588: MatMPIAIJSetPreallocation(Y,1,NULL,0,NULL);
2589: } else if (!aij->nz) {
2590: PetscInt nonew = aij->nonew;
2591: MatSeqAIJSetPreallocation(maij->A,1,NULL);
2592: aij->nonew = nonew;
2593: }
2594: MatShift_Basic(Y,a);
2595: return(0);
2596: }
2598: PetscErrorCode MatMissingDiagonal_MPIAIJ(Mat A,PetscBool *missing,PetscInt *d)
2599: {
2600: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2604: if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices");
2605: MatMissingDiagonal(a->A,missing,d);
2606: if (d) {
2607: PetscInt rstart;
2608: MatGetOwnershipRange(A,&rstart,NULL);
2609: *d += rstart;
2611: }
2612: return(0);
2613: }
2615: PetscErrorCode MatInvertVariableBlockDiagonal_MPIAIJ(Mat A,PetscInt nblocks,const PetscInt *bsizes,PetscScalar *diag)
2616: {
2617: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
2621: MatInvertVariableBlockDiagonal(a->A,nblocks,bsizes,diag);
2622: return(0);
2623: }
2625: /* -------------------------------------------------------------------*/
2626: static struct _MatOps MatOps_Values = {MatSetValues_MPIAIJ,
2627: MatGetRow_MPIAIJ,
2628: MatRestoreRow_MPIAIJ,
2629: MatMult_MPIAIJ,
2630: /* 4*/ MatMultAdd_MPIAIJ,
2631: MatMultTranspose_MPIAIJ,
2632: MatMultTransposeAdd_MPIAIJ,
2633: 0,
2634: 0,
2635: 0,
2636: /*10*/ 0,
2637: 0,
2638: 0,
2639: MatSOR_MPIAIJ,
2640: MatTranspose_MPIAIJ,
2641: /*15*/ MatGetInfo_MPIAIJ,
2642: MatEqual_MPIAIJ,
2643: MatGetDiagonal_MPIAIJ,
2644: MatDiagonalScale_MPIAIJ,
2645: MatNorm_MPIAIJ,
2646: /*20*/ MatAssemblyBegin_MPIAIJ,
2647: MatAssemblyEnd_MPIAIJ,
2648: MatSetOption_MPIAIJ,
2649: MatZeroEntries_MPIAIJ,
2650: /*24*/ MatZeroRows_MPIAIJ,
2651: 0,
2652: 0,
2653: 0,
2654: 0,
2655: /*29*/ MatSetUp_MPIAIJ,
2656: 0,
2657: 0,
2658: MatGetDiagonalBlock_MPIAIJ,
2659: 0,
2660: /*34*/ MatDuplicate_MPIAIJ,
2661: 0,
2662: 0,
2663: 0,
2664: 0,
2665: /*39*/ MatAXPY_MPIAIJ,
2666: MatCreateSubMatrices_MPIAIJ,
2667: MatIncreaseOverlap_MPIAIJ,
2668: MatGetValues_MPIAIJ,
2669: MatCopy_MPIAIJ,
2670: /*44*/ MatGetRowMax_MPIAIJ,
2671: MatScale_MPIAIJ,
2672: MatShift_MPIAIJ,
2673: MatDiagonalSet_MPIAIJ,
2674: MatZeroRowsColumns_MPIAIJ,
2675: /*49*/ MatSetRandom_MPIAIJ,
2676: 0,
2677: 0,
2678: 0,
2679: 0,
2680: /*54*/ MatFDColoringCreate_MPIXAIJ,
2681: 0,
2682: MatSetUnfactored_MPIAIJ,
2683: MatPermute_MPIAIJ,
2684: 0,
2685: /*59*/ MatCreateSubMatrix_MPIAIJ,
2686: MatDestroy_MPIAIJ,
2687: MatView_MPIAIJ,
2688: 0,
2689: MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ,
2690: /*64*/ MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ,
2691: MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ,
2692: 0,
2693: 0,
2694: 0,
2695: /*69*/ MatGetRowMaxAbs_MPIAIJ,
2696: MatGetRowMinAbs_MPIAIJ,
2697: 0,
2698: 0,
2699: 0,
2700: 0,
2701: /*75*/ MatFDColoringApply_AIJ,
2702: MatSetFromOptions_MPIAIJ,
2703: 0,
2704: 0,
2705: MatFindZeroDiagonals_MPIAIJ,
2706: /*80*/ 0,
2707: 0,
2708: 0,
2709: /*83*/ MatLoad_MPIAIJ,
2710: MatIsSymmetric_MPIAIJ,
2711: 0,
2712: 0,
2713: 0,
2714: 0,
2715: /*89*/ MatMatMult_MPIAIJ_MPIAIJ,
2716: MatMatMultSymbolic_MPIAIJ_MPIAIJ,
2717: MatMatMultNumeric_MPIAIJ_MPIAIJ,
2718: MatPtAP_MPIAIJ_MPIAIJ,
2719: MatPtAPSymbolic_MPIAIJ_MPIAIJ,
2720: /*94*/ MatPtAPNumeric_MPIAIJ_MPIAIJ,
2721: 0,
2722: 0,
2723: 0,
2724: MatPinToCPU_MPIAIJ,
2725: /*99*/ 0,
2726: 0,
2727: 0,
2728: MatConjugate_MPIAIJ,
2729: 0,
2730: /*104*/MatSetValuesRow_MPIAIJ,
2731: MatRealPart_MPIAIJ,
2732: MatImaginaryPart_MPIAIJ,
2733: 0,
2734: 0,
2735: /*109*/0,
2736: 0,
2737: MatGetRowMin_MPIAIJ,
2738: 0,
2739: MatMissingDiagonal_MPIAIJ,
2740: /*114*/MatGetSeqNonzeroStructure_MPIAIJ,
2741: 0,
2742: MatGetGhosts_MPIAIJ,
2743: 0,
2744: 0,
2745: /*119*/0,
2746: 0,
2747: 0,
2748: 0,
2749: MatGetMultiProcBlock_MPIAIJ,
2750: /*124*/MatFindNonzeroRows_MPIAIJ,
2751: MatGetColumnNorms_MPIAIJ,
2752: MatInvertBlockDiagonal_MPIAIJ,
2753: MatInvertVariableBlockDiagonal_MPIAIJ,
2754: MatCreateSubMatricesMPI_MPIAIJ,
2755: /*129*/0,
2756: MatTransposeMatMult_MPIAIJ_MPIAIJ,
2757: MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ,
2758: MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ,
2759: 0,
2760: /*134*/0,
2761: 0,
2762: MatRARt_MPIAIJ_MPIAIJ,
2763: 0,
2764: 0,
2765: /*139*/MatSetBlockSizes_MPIAIJ,
2766: 0,
2767: 0,
2768: MatFDColoringSetUp_MPIXAIJ,
2769: MatFindOffBlockDiagonalEntries_MPIAIJ,
2770: /*144*/MatCreateMPIMatConcatenateSeqMat_MPIAIJ
2771: };
2773: /* ----------------------------------------------------------------------------------------*/
2775: PetscErrorCode MatStoreValues_MPIAIJ(Mat mat)
2776: {
2777: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
2781: MatStoreValues(aij->A);
2782: MatStoreValues(aij->B);
2783: return(0);
2784: }
2786: PetscErrorCode MatRetrieveValues_MPIAIJ(Mat mat)
2787: {
2788: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
2792: MatRetrieveValues(aij->A);
2793: MatRetrieveValues(aij->B);
2794: return(0);
2795: }
2797: PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
2798: {
2799: Mat_MPIAIJ *b;
2801: PetscMPIInt size;
2804: PetscLayoutSetUp(B->rmap);
2805: PetscLayoutSetUp(B->cmap);
2806: b = (Mat_MPIAIJ*)B->data;
2808: #if defined(PETSC_USE_CTABLE)
2809: PetscTableDestroy(&b->colmap);
2810: #else
2811: PetscFree(b->colmap);
2812: #endif
2813: PetscFree(b->garray);
2814: VecDestroy(&b->lvec);
2815: VecScatterDestroy(&b->Mvctx);
2817: /* Because the B will have been resized we simply destroy it and create a new one each time */
2818: MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);
2819: MatDestroy(&b->B);
2820: MatCreate(PETSC_COMM_SELF,&b->B);
2821: MatSetSizes(b->B,B->rmap->n,size > 1 ? B->cmap->N : 0,B->rmap->n,size > 1 ? B->cmap->N : 0);
2822: MatSetBlockSizesFromMats(b->B,B,B);
2823: MatSetType(b->B,MATSEQAIJ);
2824: PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);
2826: if (!B->preallocated) {
2827: MatCreate(PETSC_COMM_SELF,&b->A);
2828: MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
2829: MatSetBlockSizesFromMats(b->A,B,B);
2830: MatSetType(b->A,MATSEQAIJ);
2831: PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);
2832: }
2834: MatSeqAIJSetPreallocation(b->A,d_nz,d_nnz);
2835: MatSeqAIJSetPreallocation(b->B,o_nz,o_nnz);
2836: B->preallocated = PETSC_TRUE;
2837: B->was_assembled = PETSC_FALSE;
2838: B->assembled = PETSC_FALSE;
2839: return(0);
2840: }
2842: PetscErrorCode MatResetPreallocation_MPIAIJ(Mat B)
2843: {
2844: Mat_MPIAIJ *b;
2849: PetscLayoutSetUp(B->rmap);
2850: PetscLayoutSetUp(B->cmap);
2851: b = (Mat_MPIAIJ*)B->data;
2853: #if defined(PETSC_USE_CTABLE)
2854: PetscTableDestroy(&b->colmap);
2855: #else
2856: PetscFree(b->colmap);
2857: #endif
2858: PetscFree(b->garray);
2859: VecDestroy(&b->lvec);
2860: VecScatterDestroy(&b->Mvctx);
2862: MatResetPreallocation(b->A);
2863: MatResetPreallocation(b->B);
2864: B->preallocated = PETSC_TRUE;
2865: B->was_assembled = PETSC_FALSE;
2866: B->assembled = PETSC_FALSE;
2867: return(0);
2868: }
2870: PetscErrorCode MatDuplicate_MPIAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
2871: {
2872: Mat mat;
2873: Mat_MPIAIJ *a,*oldmat = (Mat_MPIAIJ*)matin->data;
2877: *newmat = 0;
2878: MatCreate(PetscObjectComm((PetscObject)matin),&mat);
2879: MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
2880: MatSetBlockSizesFromMats(mat,matin,matin);
2881: MatSetType(mat,((PetscObject)matin)->type_name);
2882: a = (Mat_MPIAIJ*)mat->data;
2884: mat->factortype = matin->factortype;
2885: mat->assembled = PETSC_TRUE;
2886: mat->insertmode = NOT_SET_VALUES;
2887: mat->preallocated = PETSC_TRUE;
2889: a->size = oldmat->size;
2890: a->rank = oldmat->rank;
2891: a->donotstash = oldmat->donotstash;
2892: a->roworiented = oldmat->roworiented;
2893: a->rowindices = 0;
2894: a->rowvalues = 0;
2895: a->getrowactive = PETSC_FALSE;
2897: PetscLayoutReference(matin->rmap,&mat->rmap);
2898: PetscLayoutReference(matin->cmap,&mat->cmap);
2900: if (oldmat->colmap) {
2901: #if defined(PETSC_USE_CTABLE)
2902: PetscTableCreateCopy(oldmat->colmap,&a->colmap);
2903: #else
2904: PetscMalloc1(mat->cmap->N,&a->colmap);
2905: PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));
2906: PetscArraycpy(a->colmap,oldmat->colmap,mat->cmap->N);
2907: #endif
2908: } else a->colmap = 0;
2909: if (oldmat->garray) {
2910: PetscInt len;
2911: len = oldmat->B->cmap->n;
2912: PetscMalloc1(len+1,&a->garray);
2913: PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));
2914: if (len) { PetscArraycpy(a->garray,oldmat->garray,len); }
2915: } else a->garray = 0;
2917: VecDuplicate(oldmat->lvec,&a->lvec);
2918: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);
2919: VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
2920: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);
2922: if (oldmat->Mvctx_mpi1) {
2923: VecScatterCopy(oldmat->Mvctx_mpi1,&a->Mvctx_mpi1);
2924: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx_mpi1);
2925: }
2927: MatDuplicate(oldmat->A,cpvalues,&a->A);
2928: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
2929: MatDuplicate(oldmat->B,cpvalues,&a->B);
2930: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);
2931: PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
2932: *newmat = mat;
2933: return(0);
2934: }
2936: PetscErrorCode MatLoad_MPIAIJ(Mat newMat, PetscViewer viewer)
2937: {
2938: PetscBool isbinary, ishdf5;
2944: /* force binary viewer to load .info file if it has not yet done so */
2945: PetscViewerSetUp(viewer);
2946: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
2947: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERHDF5, &ishdf5);
2948: if (isbinary) {
2949: MatLoad_MPIAIJ_Binary(newMat,viewer);
2950: } else if (ishdf5) {
2951: #if defined(PETSC_HAVE_HDF5)
2952: MatLoad_AIJ_HDF5(newMat,viewer);
2953: #else
2954: SETERRQ(PetscObjectComm((PetscObject)newMat),PETSC_ERR_SUP,"HDF5 not supported in this build.\nPlease reconfigure using --download-hdf5");
2955: #endif
2956: } else {
2957: SETERRQ2(PetscObjectComm((PetscObject)newMat),PETSC_ERR_SUP,"Viewer type %s not yet supported for reading %s matrices",((PetscObject)viewer)->type_name,((PetscObject)newMat)->type_name);
2958: }
2959: return(0);
2960: }
2962: PetscErrorCode MatLoad_MPIAIJ_Binary(Mat newMat, PetscViewer viewer)
2963: {
2964: PetscScalar *vals,*svals;
2965: MPI_Comm comm;
2967: PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag;
2968: PetscInt i,nz,j,rstart,rend,mmax,maxnz = 0;
2969: PetscInt header[4],*rowlengths = 0,M,N,m,*cols;
2970: PetscInt *ourlens = NULL,*procsnz = NULL,*offlens = NULL,jj,*mycols,*smycols;
2971: PetscInt cend,cstart,n,*rowners;
2972: int fd;
2973: PetscInt bs = newMat->rmap->bs;
2976: PetscObjectGetComm((PetscObject)viewer,&comm);
2977: MPI_Comm_size(comm,&size);
2978: MPI_Comm_rank(comm,&rank);
2979: PetscViewerBinaryGetDescriptor(viewer,&fd);
2980: if (!rank) {
2981: PetscBinaryRead(fd,(char*)header,4,NULL,PETSC_INT);
2982: if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
2983: if (header[3] < 0) SETERRQ(PetscObjectComm((PetscObject)newMat),PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as MATMPIAIJ");
2984: }
2986: PetscOptionsBegin(comm,NULL,"Options for loading MATMPIAIJ matrix","Mat");
2987: PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);
2988: PetscOptionsEnd();
2989: if (bs < 0) bs = 1;
2991: MPI_Bcast(header+1,3,MPIU_INT,0,comm);
2992: M = header[1]; N = header[2];
2994: /* If global sizes are set, check if they are consistent with that given in the file */
2995: 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);
2996: 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);
2998: /* determine ownership of all (block) rows */
2999: if (M%bs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows (%d) and block size (%d)",M,bs);
3000: if (newMat->rmap->n < 0) m = bs*((M/bs)/size + (((M/bs) % size) > rank)); /* PETSC_DECIDE */
3001: else m = newMat->rmap->n; /* Set by user */
3003: PetscMalloc1(size+1,&rowners);
3004: MPI_Allgather(&m,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);
3006: /* First process needs enough room for process with most rows */
3007: if (!rank) {
3008: mmax = rowners[1];
3009: for (i=2; i<=size; i++) {
3010: mmax = PetscMax(mmax, rowners[i]);
3011: }
3012: } else mmax = -1; /* unused, but compilers complain */
3014: rowners[0] = 0;
3015: for (i=2; i<=size; i++) {
3016: rowners[i] += rowners[i-1];
3017: }
3018: rstart = rowners[rank];
3019: rend = rowners[rank+1];
3021: /* distribute row lengths to all processors */
3022: PetscMalloc2(m,&ourlens,m,&offlens);
3023: if (!rank) {
3024: PetscBinaryRead(fd,ourlens,m,NULL,PETSC_INT);
3025: PetscMalloc1(mmax,&rowlengths);
3026: PetscCalloc1(size,&procsnz);
3027: for (j=0; j<m; j++) {
3028: procsnz[0] += ourlens[j];
3029: }
3030: for (i=1; i<size; i++) {
3031: PetscBinaryRead(fd,rowlengths,rowners[i+1]-rowners[i],NULL,PETSC_INT);
3032: /* calculate the number of nonzeros on each processor */
3033: for (j=0; j<rowners[i+1]-rowners[i]; j++) {
3034: procsnz[i] += rowlengths[j];
3035: }
3036: MPIULong_Send(rowlengths,rowners[i+1]-rowners[i],MPIU_INT,i,tag,comm);
3037: }
3038: PetscFree(rowlengths);
3039: } else {
3040: MPIULong_Recv(ourlens,m,MPIU_INT,0,tag,comm);
3041: }
3043: if (!rank) {
3044: /* determine max buffer needed and allocate it */
3045: maxnz = 0;
3046: for (i=0; i<size; i++) {
3047: maxnz = PetscMax(maxnz,procsnz[i]);
3048: }
3049: PetscMalloc1(maxnz,&cols);
3051: /* read in my part of the matrix column indices */
3052: nz = procsnz[0];
3053: PetscMalloc1(nz,&mycols);
3054: PetscBinaryRead(fd,mycols,nz,NULL,PETSC_INT);
3056: /* read in every one elses and ship off */
3057: for (i=1; i<size; i++) {
3058: nz = procsnz[i];
3059: PetscBinaryRead(fd,cols,nz,NULL,PETSC_INT);
3060: MPIULong_Send(cols,nz,MPIU_INT,i,tag,comm);
3061: }
3062: PetscFree(cols);
3063: } else {
3064: /* determine buffer space needed for message */
3065: nz = 0;
3066: for (i=0; i<m; i++) {
3067: nz += ourlens[i];
3068: }
3069: PetscMalloc1(nz,&mycols);
3071: /* receive message of column indices*/
3072: MPIULong_Recv(mycols,nz,MPIU_INT,0,tag,comm);
3073: }
3075: /* determine column ownership if matrix is not square */
3076: if (N != M) {
3077: if (newMat->cmap->n < 0) n = N/size + ((N % size) > rank);
3078: else n = newMat->cmap->n;
3079: MPI_Scan(&n,&cend,1,MPIU_INT,MPI_SUM,comm);
3080: cstart = cend - n;
3081: } else {
3082: cstart = rstart;
3083: cend = rend;
3084: n = cend - cstart;
3085: }
3087: /* loop over local rows, determining number of off diagonal entries */
3088: PetscArrayzero(offlens,m);
3089: jj = 0;
3090: for (i=0; i<m; i++) {
3091: for (j=0; j<ourlens[i]; j++) {
3092: if (mycols[jj] < cstart || mycols[jj] >= cend) offlens[i]++;
3093: jj++;
3094: }
3095: }
3097: for (i=0; i<m; i++) {
3098: ourlens[i] -= offlens[i];
3099: }
3100: MatSetSizes(newMat,m,n,M,N);
3102: if (bs > 1) {MatSetBlockSize(newMat,bs);}
3104: MatMPIAIJSetPreallocation(newMat,0,ourlens,0,offlens);
3106: for (i=0; i<m; i++) {
3107: ourlens[i] += offlens[i];
3108: }
3110: if (!rank) {
3111: PetscMalloc1(maxnz+1,&vals);
3113: /* read in my part of the matrix numerical values */
3114: nz = procsnz[0];
3115: PetscBinaryRead(fd,vals,nz,NULL,PETSC_SCALAR);
3117: /* insert into matrix */
3118: jj = rstart;
3119: smycols = mycols;
3120: svals = vals;
3121: for (i=0; i<m; i++) {
3122: MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);
3123: smycols += ourlens[i];
3124: svals += ourlens[i];
3125: jj++;
3126: }
3128: /* read in other processors and ship out */
3129: for (i=1; i<size; i++) {
3130: nz = procsnz[i];
3131: PetscBinaryRead(fd,vals,nz,NULL,PETSC_SCALAR);
3132: MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newMat)->tag,comm);
3133: }
3134: PetscFree(procsnz);
3135: } else {
3136: /* receive numeric values */
3137: PetscMalloc1(nz+1,&vals);
3139: /* receive message of values*/
3140: MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newMat)->tag,comm);
3142: /* insert into matrix */
3143: jj = rstart;
3144: smycols = mycols;
3145: svals = vals;
3146: for (i=0; i<m; i++) {
3147: MatSetValues_MPIAIJ(newMat,1,&jj,ourlens[i],smycols,svals,INSERT_VALUES);
3148: smycols += ourlens[i];
3149: svals += ourlens[i];
3150: jj++;
3151: }
3152: }
3153: PetscFree2(ourlens,offlens);
3154: PetscFree(vals);
3155: PetscFree(mycols);
3156: PetscFree(rowners);
3157: MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);
3158: MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);
3159: return(0);
3160: }
3162: /* Not scalable because of ISAllGather() unless getting all columns. */
3163: PetscErrorCode ISGetSeqIS_Private(Mat mat,IS iscol,IS *isseq)
3164: {
3166: IS iscol_local;
3167: PetscBool isstride;
3168: PetscMPIInt lisstride=0,gisstride;
3171: /* check if we are grabbing all columns*/
3172: PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&isstride);
3174: if (isstride) {
3175: PetscInt start,len,mstart,mlen;
3176: ISStrideGetInfo(iscol,&start,NULL);
3177: ISGetLocalSize(iscol,&len);
3178: MatGetOwnershipRangeColumn(mat,&mstart,&mlen);
3179: if (mstart == start && mlen-mstart == len) lisstride = 1;
3180: }
3182: MPIU_Allreduce(&lisstride,&gisstride,1,MPI_INT,MPI_MIN,PetscObjectComm((PetscObject)mat));
3183: if (gisstride) {
3184: PetscInt N;
3185: MatGetSize(mat,NULL,&N);
3186: ISCreateStride(PetscObjectComm((PetscObject)mat),N,0,1,&iscol_local);
3187: ISSetIdentity(iscol_local);
3188: PetscInfo(mat,"Optimizing for obtaining all columns of the matrix; skipping ISAllGather()\n");
3189: } else {
3190: PetscInt cbs;
3191: ISGetBlockSize(iscol,&cbs);
3192: ISAllGather(iscol,&iscol_local);
3193: ISSetBlockSize(iscol_local,cbs);
3194: }
3196: *isseq = iscol_local;
3197: return(0);
3198: }
3200: /*
3201: Used by MatCreateSubMatrix_MPIAIJ_SameRowColDist() to avoid ISAllGather() and global size of iscol_local
3202: (see MatCreateSubMatrix_MPIAIJ_nonscalable)
3204: Input Parameters:
3205: mat - matrix
3206: isrow - parallel row index set; its local indices are a subset of local columns of mat,
3207: i.e., mat->rstart <= isrow[i] < mat->rend
3208: iscol - parallel column index set; its local indices are a subset of local columns of mat,
3209: i.e., mat->cstart <= iscol[i] < mat->cend
3210: Output Parameter:
3211: isrow_d,iscol_d - sequential row and column index sets for retrieving mat->A
3212: iscol_o - sequential column index set for retrieving mat->B
3213: garray - column map; garray[i] indicates global location of iscol_o[i] in iscol
3214: */
3215: PetscErrorCode ISGetSeqIS_SameColDist_Private(Mat mat,IS isrow,IS iscol,IS *isrow_d,IS *iscol_d,IS *iscol_o,const PetscInt *garray[])
3216: {
3218: Vec x,cmap;
3219: const PetscInt *is_idx;
3220: PetscScalar *xarray,*cmaparray;
3221: PetscInt ncols,isstart,*idx,m,rstart,*cmap1,count;
3222: Mat_MPIAIJ *a=(Mat_MPIAIJ*)mat->data;
3223: Mat B=a->B;
3224: Vec lvec=a->lvec,lcmap;
3225: PetscInt i,cstart,cend,Bn=B->cmap->N;
3226: MPI_Comm comm;
3227: VecScatter Mvctx=a->Mvctx;
3230: PetscObjectGetComm((PetscObject)mat,&comm);
3231: ISGetLocalSize(iscol,&ncols);
3233: /* (1) iscol is a sub-column vector of mat, pad it with '-1.' to form a full vector x */
3234: MatCreateVecs(mat,&x,NULL);
3235: VecSet(x,-1.0);
3236: VecDuplicate(x,&cmap);
3237: VecSet(cmap,-1.0);
3239: /* Get start indices */
3240: MPI_Scan(&ncols,&isstart,1,MPIU_INT,MPI_SUM,comm);
3241: isstart -= ncols;
3242: MatGetOwnershipRangeColumn(mat,&cstart,&cend);
3244: ISGetIndices(iscol,&is_idx);
3245: VecGetArray(x,&xarray);
3246: VecGetArray(cmap,&cmaparray);
3247: PetscMalloc1(ncols,&idx);
3248: for (i=0; i<ncols; i++) {
3249: xarray[is_idx[i]-cstart] = (PetscScalar)is_idx[i];
3250: cmaparray[is_idx[i]-cstart] = i + isstart; /* global index of iscol[i] */
3251: idx[i] = is_idx[i]-cstart; /* local index of iscol[i] */
3252: }
3253: VecRestoreArray(x,&xarray);
3254: VecRestoreArray(cmap,&cmaparray);
3255: ISRestoreIndices(iscol,&is_idx);
3257: /* Get iscol_d */
3258: ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,iscol_d);
3259: ISGetBlockSize(iscol,&i);
3260: ISSetBlockSize(*iscol_d,i);
3262: /* Get isrow_d */
3263: ISGetLocalSize(isrow,&m);
3264: rstart = mat->rmap->rstart;
3265: PetscMalloc1(m,&idx);
3266: ISGetIndices(isrow,&is_idx);
3267: for (i=0; i<m; i++) idx[i] = is_idx[i]-rstart;
3268: ISRestoreIndices(isrow,&is_idx);
3270: ISCreateGeneral(PETSC_COMM_SELF,m,idx,PETSC_OWN_POINTER,isrow_d);
3271: ISGetBlockSize(isrow,&i);
3272: ISSetBlockSize(*isrow_d,i);
3274: /* (2) Scatter x and cmap using aij->Mvctx to get their off-process portions (see MatMult_MPIAIJ) */
3275: VecScatterBegin(Mvctx,x,lvec,INSERT_VALUES,SCATTER_FORWARD);
3276: VecScatterEnd(Mvctx,x,lvec,INSERT_VALUES,SCATTER_FORWARD);
3278: VecDuplicate(lvec,&lcmap);
3280: VecScatterBegin(Mvctx,cmap,lcmap,INSERT_VALUES,SCATTER_FORWARD);
3281: VecScatterEnd(Mvctx,cmap,lcmap,INSERT_VALUES,SCATTER_FORWARD);
3283: /* (3) create sequential iscol_o (a subset of iscol) and isgarray */
3284: /* off-process column indices */
3285: count = 0;
3286: PetscMalloc1(Bn,&idx);
3287: PetscMalloc1(Bn,&cmap1);
3289: VecGetArray(lvec,&xarray);
3290: VecGetArray(lcmap,&cmaparray);
3291: for (i=0; i<Bn; i++) {
3292: if (PetscRealPart(xarray[i]) > -1.0) {
3293: idx[count] = i; /* local column index in off-diagonal part B */
3294: cmap1[count] = (PetscInt)PetscRealPart(cmaparray[i]); /* column index in submat */
3295: count++;
3296: }
3297: }
3298: VecRestoreArray(lvec,&xarray);
3299: VecRestoreArray(lcmap,&cmaparray);
3301: ISCreateGeneral(PETSC_COMM_SELF,count,idx,PETSC_COPY_VALUES,iscol_o);
3302: /* cannot ensure iscol_o has same blocksize as iscol! */
3304: PetscFree(idx);
3305: *garray = cmap1;
3307: VecDestroy(&x);
3308: VecDestroy(&cmap);
3309: VecDestroy(&lcmap);
3310: return(0);
3311: }
3313: /* isrow and iscol have same processor distribution as mat, output *submat is a submatrix of local mat */
3314: PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameRowColDist(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *submat)
3315: {
3317: Mat_MPIAIJ *a = (Mat_MPIAIJ*)mat->data,*asub;
3318: Mat M = NULL;
3319: MPI_Comm comm;
3320: IS iscol_d,isrow_d,iscol_o;
3321: Mat Asub = NULL,Bsub = NULL;
3322: PetscInt n;
3325: PetscObjectGetComm((PetscObject)mat,&comm);
3327: if (call == MAT_REUSE_MATRIX) {
3328: /* Retrieve isrow_d, iscol_d and iscol_o from submat */
3329: PetscObjectQuery((PetscObject)*submat,"isrow_d",(PetscObject*)&isrow_d);
3330: if (!isrow_d) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"isrow_d passed in was not used before, cannot reuse");
3332: PetscObjectQuery((PetscObject)*submat,"iscol_d",(PetscObject*)&iscol_d);
3333: if (!iscol_d) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"iscol_d passed in was not used before, cannot reuse");
3335: PetscObjectQuery((PetscObject)*submat,"iscol_o",(PetscObject*)&iscol_o);
3336: if (!iscol_o) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"iscol_o passed in was not used before, cannot reuse");
3338: /* Update diagonal and off-diagonal portions of submat */
3339: asub = (Mat_MPIAIJ*)(*submat)->data;
3340: MatCreateSubMatrix_SeqAIJ(a->A,isrow_d,iscol_d,PETSC_DECIDE,MAT_REUSE_MATRIX,&asub->A);
3341: ISGetLocalSize(iscol_o,&n);
3342: if (n) {
3343: MatCreateSubMatrix_SeqAIJ(a->B,isrow_d,iscol_o,PETSC_DECIDE,MAT_REUSE_MATRIX,&asub->B);
3344: }
3345: MatAssemblyBegin(*submat,MAT_FINAL_ASSEMBLY);
3346: MatAssemblyEnd(*submat,MAT_FINAL_ASSEMBLY);
3348: } else { /* call == MAT_INITIAL_MATRIX) */
3349: const PetscInt *garray;
3350: PetscInt BsubN;
3352: /* Create isrow_d, iscol_d, iscol_o and isgarray (replace isgarray with array?) */
3353: ISGetSeqIS_SameColDist_Private(mat,isrow,iscol,&isrow_d,&iscol_d,&iscol_o,&garray);
3355: /* Create local submatrices Asub and Bsub */
3356: MatCreateSubMatrix_SeqAIJ(a->A,isrow_d,iscol_d,PETSC_DECIDE,MAT_INITIAL_MATRIX,&Asub);
3357: MatCreateSubMatrix_SeqAIJ(a->B,isrow_d,iscol_o,PETSC_DECIDE,MAT_INITIAL_MATRIX,&Bsub);
3359: /* Create submatrix M */
3360: MatCreateMPIAIJWithSeqAIJ(comm,Asub,Bsub,garray,&M);
3362: /* If Bsub has empty columns, compress iscol_o such that it will retrieve condensed Bsub from a->B during reuse */
3363: asub = (Mat_MPIAIJ*)M->data;
3365: ISGetLocalSize(iscol_o,&BsubN);
3366: n = asub->B->cmap->N;
3367: if (BsubN > n) {
3368: /* This case can be tested using ~petsc/src/tao/bound/examples/tutorials/runplate2_3 */
3369: const PetscInt *idx;
3370: PetscInt i,j,*idx_new,*subgarray = asub->garray;
3371: PetscInfo2(M,"submatrix Bn %D != BsubN %D, update iscol_o\n",n,BsubN);
3373: PetscMalloc1(n,&idx_new);
3374: j = 0;
3375: ISGetIndices(iscol_o,&idx);
3376: for (i=0; i<n; i++) {
3377: if (j >= BsubN) break;
3378: while (subgarray[i] > garray[j]) j++;
3380: if (subgarray[i] == garray[j]) {
3381: idx_new[i] = idx[j++];
3382: } else SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"subgarray[%D]=%D cannot < garray[%D]=%D",i,subgarray[i],j,garray[j]);
3383: }
3384: ISRestoreIndices(iscol_o,&idx);
3386: ISDestroy(&iscol_o);
3387: ISCreateGeneral(PETSC_COMM_SELF,n,idx_new,PETSC_OWN_POINTER,&iscol_o);
3389: } else if (BsubN < n) {
3390: SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Columns of Bsub cannot be smaller than B's",BsubN,asub->B->cmap->N);
3391: }
3393: PetscFree(garray);
3394: *submat = M;
3396: /* Save isrow_d, iscol_d and iscol_o used in processor for next request */
3397: PetscObjectCompose((PetscObject)M,"isrow_d",(PetscObject)isrow_d);
3398: ISDestroy(&isrow_d);
3400: PetscObjectCompose((PetscObject)M,"iscol_d",(PetscObject)iscol_d);
3401: ISDestroy(&iscol_d);
3403: PetscObjectCompose((PetscObject)M,"iscol_o",(PetscObject)iscol_o);
3404: ISDestroy(&iscol_o);
3405: }
3406: return(0);
3407: }
3409: PetscErrorCode MatCreateSubMatrix_MPIAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
3410: {
3412: IS iscol_local=NULL,isrow_d;
3413: PetscInt csize;
3414: PetscInt n,i,j,start,end;
3415: PetscBool sameRowDist=PETSC_FALSE,sameDist[2],tsameDist[2];
3416: MPI_Comm comm;
3419: /* If isrow has same processor distribution as mat,
3420: call MatCreateSubMatrix_MPIAIJ_SameRowDist() to avoid using a hash table with global size of iscol */
3421: if (call == MAT_REUSE_MATRIX) {
3422: PetscObjectQuery((PetscObject)*newmat,"isrow_d",(PetscObject*)&isrow_d);
3423: if (isrow_d) {
3424: sameRowDist = PETSC_TRUE;
3425: tsameDist[1] = PETSC_TRUE; /* sameColDist */
3426: } else {
3427: PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_local);
3428: if (iscol_local) {
3429: sameRowDist = PETSC_TRUE;
3430: tsameDist[1] = PETSC_FALSE; /* !sameColDist */
3431: }
3432: }
3433: } else {
3434: /* Check if isrow has same processor distribution as mat */
3435: sameDist[0] = PETSC_FALSE;
3436: ISGetLocalSize(isrow,&n);
3437: if (!n) {
3438: sameDist[0] = PETSC_TRUE;
3439: } else {
3440: ISGetMinMax(isrow,&i,&j);
3441: MatGetOwnershipRange(mat,&start,&end);
3442: if (i >= start && j < end) {
3443: sameDist[0] = PETSC_TRUE;
3444: }
3445: }
3447: /* Check if iscol has same processor distribution as mat */
3448: sameDist[1] = PETSC_FALSE;
3449: ISGetLocalSize(iscol,&n);
3450: if (!n) {
3451: sameDist[1] = PETSC_TRUE;
3452: } else {
3453: ISGetMinMax(iscol,&i,&j);
3454: MatGetOwnershipRangeColumn(mat,&start,&end);
3455: if (i >= start && j < end) sameDist[1] = PETSC_TRUE;
3456: }
3458: PetscObjectGetComm((PetscObject)mat,&comm);
3459: MPIU_Allreduce(&sameDist,&tsameDist,2,MPIU_BOOL,MPI_LAND,comm);
3460: sameRowDist = tsameDist[0];
3461: }
3463: if (sameRowDist) {
3464: if (tsameDist[1]) { /* sameRowDist & sameColDist */
3465: /* isrow and iscol have same processor distribution as mat */
3466: MatCreateSubMatrix_MPIAIJ_SameRowColDist(mat,isrow,iscol,call,newmat);
3467: return(0);
3468: } else { /* sameRowDist */
3469: /* isrow has same processor distribution as mat */
3470: if (call == MAT_INITIAL_MATRIX) {
3471: PetscBool sorted;
3472: ISGetSeqIS_Private(mat,iscol,&iscol_local);
3473: ISGetLocalSize(iscol_local,&n); /* local size of iscol_local = global columns of newmat */
3474: ISGetSize(iscol,&i);
3475: if (n != i) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"n %d != size of iscol %d",n,i);
3477: ISSorted(iscol_local,&sorted);
3478: if (sorted) {
3479: /* MatCreateSubMatrix_MPIAIJ_SameRowDist() requires iscol_local be sorted; it can have duplicate indices */
3480: MatCreateSubMatrix_MPIAIJ_SameRowDist(mat,isrow,iscol,iscol_local,MAT_INITIAL_MATRIX,newmat);
3481: return(0);
3482: }
3483: } else { /* call == MAT_REUSE_MATRIX */
3484: IS iscol_sub;
3485: PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_sub);
3486: if (iscol_sub) {
3487: MatCreateSubMatrix_MPIAIJ_SameRowDist(mat,isrow,iscol,NULL,call,newmat);
3488: return(0);
3489: }
3490: }
3491: }
3492: }
3494: /* General case: iscol -> iscol_local which has global size of iscol */
3495: if (call == MAT_REUSE_MATRIX) {
3496: PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);
3497: if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
3498: } else {
3499: if (!iscol_local) {
3500: ISGetSeqIS_Private(mat,iscol,&iscol_local);
3501: }
3502: }
3504: ISGetLocalSize(iscol,&csize);
3505: MatCreateSubMatrix_MPIAIJ_nonscalable(mat,isrow,iscol_local,csize,call,newmat);
3507: if (call == MAT_INITIAL_MATRIX) {
3508: PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);
3509: ISDestroy(&iscol_local);
3510: }
3511: return(0);
3512: }
3514: /*@C
3515: MatCreateMPIAIJWithSeqAIJ - creates a MPIAIJ matrix using SeqAIJ matrices that contain the "diagonal"
3516: and "off-diagonal" part of the matrix in CSR format.
3518: Collective
3520: Input Parameters:
3521: + comm - MPI communicator
3522: . A - "diagonal" portion of matrix
3523: . B - "off-diagonal" portion of matrix, may have empty columns, will be destroyed by this routine
3524: - garray - global index of B columns
3526: Output Parameter:
3527: . mat - the matrix, with input A as its local diagonal matrix
3528: Level: advanced
3530: Notes:
3531: See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix.
3532: A becomes part of output mat, B is destroyed by this routine. The user cannot use A and B anymore.
3534: .seealso: MatCreateMPIAIJWithSplitArrays()
3535: @*/
3536: PetscErrorCode MatCreateMPIAIJWithSeqAIJ(MPI_Comm comm,Mat A,Mat B,const PetscInt garray[],Mat *mat)
3537: {
3539: Mat_MPIAIJ *maij;
3540: Mat_SeqAIJ *b=(Mat_SeqAIJ*)B->data,*bnew;
3541: PetscInt *oi=b->i,*oj=b->j,i,nz,col;
3542: PetscScalar *oa=b->a;
3543: Mat Bnew;
3544: PetscInt m,n,N;
3547: MatCreate(comm,mat);
3548: MatGetSize(A,&m,&n);
3549: if (m != B->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Am %D != Bm %D",m,B->rmap->N);
3550: 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);
3551: /* remove check below; When B is created using iscol_o from ISGetSeqIS_SameColDist_Private(), its bs may not be same as A */
3552: /* 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); */
3554: /* Get global columns of mat */
3555: MPIU_Allreduce(&n,&N,1,MPIU_INT,MPI_SUM,comm);
3557: MatSetSizes(*mat,m,n,PETSC_DECIDE,N);
3558: MatSetType(*mat,MATMPIAIJ);
3559: MatSetBlockSizes(*mat,A->rmap->bs,A->cmap->bs);
3560: maij = (Mat_MPIAIJ*)(*mat)->data;
3562: (*mat)->preallocated = PETSC_TRUE;
3564: PetscLayoutSetUp((*mat)->rmap);
3565: PetscLayoutSetUp((*mat)->cmap);
3567: /* Set A as diagonal portion of *mat */
3568: maij->A = A;
3570: nz = oi[m];
3571: for (i=0; i<nz; i++) {
3572: col = oj[i];
3573: oj[i] = garray[col];
3574: }
3576: /* Set Bnew as off-diagonal portion of *mat */
3577: MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,N,oi,oj,oa,&Bnew);
3578: bnew = (Mat_SeqAIJ*)Bnew->data;
3579: bnew->maxnz = b->maxnz; /* allocated nonzeros of B */
3580: maij->B = Bnew;
3582: if (B->rmap->N != Bnew->rmap->N) SETERRQ2(PETSC_COMM_SELF,0,"BN %d != BnewN %d",B->rmap->N,Bnew->rmap->N);
3584: b->singlemalloc = PETSC_FALSE; /* B arrays are shared by Bnew */
3585: b->free_a = PETSC_FALSE;
3586: b->free_ij = PETSC_FALSE;
3587: MatDestroy(&B);
3589: bnew->singlemalloc = PETSC_TRUE; /* arrays will be freed by MatDestroy(&Bnew) */
3590: bnew->free_a = PETSC_TRUE;
3591: bnew->free_ij = PETSC_TRUE;
3593: /* condense columns of maij->B */
3594: MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);
3595: MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);
3596: MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);
3597: MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_FALSE);
3598: MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
3599: return(0);
3600: }
3602: extern PetscErrorCode MatCreateSubMatrices_MPIAIJ_SingleIS_Local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool,Mat*);
3604: PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameRowDist(Mat mat,IS isrow,IS iscol,IS iscol_local,MatReuse call,Mat *newmat)
3605: {
3607: PetscInt i,m,n,rstart,row,rend,nz,j,bs,cbs;
3608: PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal;
3609: Mat_MPIAIJ *a=(Mat_MPIAIJ*)mat->data;
3610: Mat M,Msub,B=a->B;
3611: MatScalar *aa;
3612: Mat_SeqAIJ *aij;
3613: PetscInt *garray = a->garray,*colsub,Ncols;
3614: PetscInt count,Bn=B->cmap->N,cstart=mat->cmap->rstart,cend=mat->cmap->rend;
3615: IS iscol_sub,iscmap;
3616: const PetscInt *is_idx,*cmap;
3617: PetscBool allcolumns=PETSC_FALSE;
3618: MPI_Comm comm;
3621: PetscObjectGetComm((PetscObject)mat,&comm);
3623: if (call == MAT_REUSE_MATRIX) {
3624: PetscObjectQuery((PetscObject)*newmat,"SubIScol",(PetscObject*)&iscol_sub);
3625: if (!iscol_sub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"SubIScol passed in was not used before, cannot reuse");
3626: ISGetLocalSize(iscol_sub,&count);
3628: PetscObjectQuery((PetscObject)*newmat,"Subcmap",(PetscObject*)&iscmap);
3629: if (!iscmap) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Subcmap passed in was not used before, cannot reuse");
3631: PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Msub);
3632: if (!Msub) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
3634: MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_REUSE_MATRIX,PETSC_FALSE,&Msub);
3636: } else { /* call == MAT_INITIAL_MATRIX) */
3637: PetscBool flg;
3639: ISGetLocalSize(iscol,&n);
3640: ISGetSize(iscol,&Ncols);
3642: /* (1) iscol -> nonscalable iscol_local */
3643: /* Check for special case: each processor gets entire matrix columns */
3644: ISIdentity(iscol_local,&flg);
3645: if (flg && n == mat->cmap->N) allcolumns = PETSC_TRUE;
3646: if (allcolumns) {
3647: iscol_sub = iscol_local;
3648: PetscObjectReference((PetscObject)iscol_local);
3649: ISCreateStride(PETSC_COMM_SELF,n,0,1,&iscmap);
3651: } else {
3652: /* (2) iscol_local -> iscol_sub and iscmap. Implementation below requires iscol_local be sorted, it can have duplicate indices */
3653: PetscInt *idx,*cmap1,k;
3654: PetscMalloc1(Ncols,&idx);
3655: PetscMalloc1(Ncols,&cmap1);
3656: ISGetIndices(iscol_local,&is_idx);
3657: count = 0;
3658: k = 0;
3659: for (i=0; i<Ncols; i++) {
3660: j = is_idx[i];
3661: if (j >= cstart && j < cend) {
3662: /* diagonal part of mat */
3663: idx[count] = j;
3664: cmap1[count++] = i; /* column index in submat */
3665: } else if (Bn) {
3666: /* off-diagonal part of mat */
3667: if (j == garray[k]) {
3668: idx[count] = j;
3669: cmap1[count++] = i; /* column index in submat */
3670: } else if (j > garray[k]) {
3671: while (j > garray[k] && k < Bn-1) k++;
3672: if (j == garray[k]) {
3673: idx[count] = j;
3674: cmap1[count++] = i; /* column index in submat */
3675: }
3676: }
3677: }
3678: }
3679: ISRestoreIndices(iscol_local,&is_idx);
3681: ISCreateGeneral(PETSC_COMM_SELF,count,idx,PETSC_OWN_POINTER,&iscol_sub);
3682: ISGetBlockSize(iscol,&cbs);
3683: ISSetBlockSize(iscol_sub,cbs);
3685: ISCreateGeneral(PetscObjectComm((PetscObject)iscol_local),count,cmap1,PETSC_OWN_POINTER,&iscmap);
3686: }
3688: /* (3) Create sequential Msub */
3689: MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol_sub,MAT_INITIAL_MATRIX,allcolumns,&Msub);
3690: }
3692: ISGetLocalSize(iscol_sub,&count);
3693: aij = (Mat_SeqAIJ*)(Msub)->data;
3694: ii = aij->i;
3695: ISGetIndices(iscmap,&cmap);
3697: /*
3698: m - number of local rows
3699: Ncols - number of columns (same on all processors)
3700: rstart - first row in new global matrix generated
3701: */
3702: MatGetSize(Msub,&m,NULL);
3704: if (call == MAT_INITIAL_MATRIX) {
3705: /* (4) Create parallel newmat */
3706: PetscMPIInt rank,size;
3707: PetscInt csize;
3709: MPI_Comm_size(comm,&size);
3710: MPI_Comm_rank(comm,&rank);
3712: /*
3713: Determine the number of non-zeros in the diagonal and off-diagonal
3714: portions of the matrix in order to do correct preallocation
3715: */
3717: /* first get start and end of "diagonal" columns */
3718: ISGetLocalSize(iscol,&csize);
3719: if (csize == PETSC_DECIDE) {
3720: ISGetSize(isrow,&mglobal);
3721: if (mglobal == Ncols) { /* square matrix */
3722: nlocal = m;
3723: } else {
3724: nlocal = Ncols/size + ((Ncols % size) > rank);
3725: }
3726: } else {
3727: nlocal = csize;
3728: }
3729: MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);
3730: rstart = rend - nlocal;
3731: 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);
3733: /* next, compute all the lengths */
3734: jj = aij->j;
3735: PetscMalloc1(2*m+1,&dlens);
3736: olens = dlens + m;
3737: for (i=0; i<m; i++) {
3738: jend = ii[i+1] - ii[i];
3739: olen = 0;
3740: dlen = 0;
3741: for (j=0; j<jend; j++) {
3742: if (cmap[*jj] < rstart || cmap[*jj] >= rend) olen++;
3743: else dlen++;
3744: jj++;
3745: }
3746: olens[i] = olen;
3747: dlens[i] = dlen;
3748: }
3750: ISGetBlockSize(isrow,&bs);
3751: ISGetBlockSize(iscol,&cbs);
3753: MatCreate(comm,&M);
3754: MatSetSizes(M,m,nlocal,PETSC_DECIDE,Ncols);
3755: MatSetBlockSizes(M,bs,cbs);
3756: MatSetType(M,((PetscObject)mat)->type_name);
3757: MatMPIAIJSetPreallocation(M,0,dlens,0,olens);
3758: PetscFree(dlens);
3760: } else { /* call == MAT_REUSE_MATRIX */
3761: M = *newmat;
3762: MatGetLocalSize(M,&i,NULL);
3763: if (i != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request");
3764: MatZeroEntries(M);
3765: /*
3766: The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly,
3767: rather than the slower MatSetValues().
3768: */
3769: M->was_assembled = PETSC_TRUE;
3770: M->assembled = PETSC_FALSE;
3771: }
3773: /* (5) Set values of Msub to *newmat */
3774: PetscMalloc1(count,&colsub);
3775: MatGetOwnershipRange(M,&rstart,NULL);
3777: jj = aij->j;
3778: aa = aij->a;
3779: for (i=0; i<m; i++) {
3780: row = rstart + i;
3781: nz = ii[i+1] - ii[i];
3782: for (j=0; j<nz; j++) colsub[j] = cmap[jj[j]];
3783: MatSetValues_MPIAIJ(M,1,&row,nz,colsub,aa,INSERT_VALUES);
3784: jj += nz; aa += nz;
3785: }
3786: ISRestoreIndices(iscmap,&cmap);
3788: MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
3789: MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);
3791: PetscFree(colsub);
3793: /* save Msub, iscol_sub and iscmap used in processor for next request */
3794: if (call == MAT_INITIAL_MATRIX) {
3795: *newmat = M;
3796: PetscObjectCompose((PetscObject)(*newmat),"SubMatrix",(PetscObject)Msub);
3797: MatDestroy(&Msub);
3799: PetscObjectCompose((PetscObject)(*newmat),"SubIScol",(PetscObject)iscol_sub);
3800: ISDestroy(&iscol_sub);
3802: PetscObjectCompose((PetscObject)(*newmat),"Subcmap",(PetscObject)iscmap);
3803: ISDestroy(&iscmap);
3805: if (iscol_local) {
3806: PetscObjectCompose((PetscObject)(*newmat),"ISAllGather",(PetscObject)iscol_local);
3807: ISDestroy(&iscol_local);
3808: }
3809: }
3810: return(0);
3811: }
3813: /*
3814: Not great since it makes two copies of the submatrix, first an SeqAIJ
3815: in local and then by concatenating the local matrices the end result.
3816: Writing it directly would be much like MatCreateSubMatrices_MPIAIJ()
3818: Note: This requires a sequential iscol with all indices.
3819: */
3820: PetscErrorCode MatCreateSubMatrix_MPIAIJ_nonscalable(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat)
3821: {
3823: PetscMPIInt rank,size;
3824: PetscInt i,m,n,rstart,row,rend,nz,*cwork,j,bs,cbs;
3825: PetscInt *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal;
3826: Mat M,Mreuse;
3827: MatScalar *aa,*vwork;
3828: MPI_Comm comm;
3829: Mat_SeqAIJ *aij;
3830: PetscBool colflag,allcolumns=PETSC_FALSE;
3833: PetscObjectGetComm((PetscObject)mat,&comm);
3834: MPI_Comm_rank(comm,&rank);
3835: MPI_Comm_size(comm,&size);
3837: /* Check for special case: each processor gets entire matrix columns */
3838: ISIdentity(iscol,&colflag);
3839: ISGetLocalSize(iscol,&n);
3840: if (colflag && n == mat->cmap->N) allcolumns = PETSC_TRUE;
3842: if (call == MAT_REUSE_MATRIX) {
3843: PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);
3844: if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
3845: MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,allcolumns,&Mreuse);
3846: } else {
3847: MatCreateSubMatrices_MPIAIJ_SingleIS_Local(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,allcolumns,&Mreuse);
3848: }
3850: /*
3851: m - number of local rows
3852: n - number of columns (same on all processors)
3853: rstart - first row in new global matrix generated
3854: */
3855: MatGetSize(Mreuse,&m,&n);
3856: MatGetBlockSizes(Mreuse,&bs,&cbs);
3857: if (call == MAT_INITIAL_MATRIX) {
3858: aij = (Mat_SeqAIJ*)(Mreuse)->data;
3859: ii = aij->i;
3860: jj = aij->j;
3862: /*
3863: Determine the number of non-zeros in the diagonal and off-diagonal
3864: portions of the matrix in order to do correct preallocation
3865: */
3867: /* first get start and end of "diagonal" columns */
3868: if (csize == PETSC_DECIDE) {
3869: ISGetSize(isrow,&mglobal);
3870: if (mglobal == n) { /* square matrix */
3871: nlocal = m;
3872: } else {
3873: nlocal = n/size + ((n % size) > rank);
3874: }
3875: } else {
3876: nlocal = csize;
3877: }
3878: MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);
3879: rstart = rend - nlocal;
3880: 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);
3882: /* next, compute all the lengths */
3883: PetscMalloc1(2*m+1,&dlens);
3884: olens = dlens + m;
3885: for (i=0; i<m; i++) {
3886: jend = ii[i+1] - ii[i];
3887: olen = 0;
3888: dlen = 0;
3889: for (j=0; j<jend; j++) {
3890: if (*jj < rstart || *jj >= rend) olen++;
3891: else dlen++;
3892: jj++;
3893: }
3894: olens[i] = olen;
3895: dlens[i] = dlen;
3896: }
3897: MatCreate(comm,&M);
3898: MatSetSizes(M,m,nlocal,PETSC_DECIDE,n);
3899: MatSetBlockSizes(M,bs,cbs);
3900: MatSetType(M,((PetscObject)mat)->type_name);
3901: MatMPIAIJSetPreallocation(M,0,dlens,0,olens);
3902: PetscFree(dlens);
3903: } else {
3904: PetscInt ml,nl;
3906: M = *newmat;
3907: MatGetLocalSize(M,&ml,&nl);
3908: if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request");
3909: MatZeroEntries(M);
3910: /*
3911: The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly,
3912: rather than the slower MatSetValues().
3913: */
3914: M->was_assembled = PETSC_TRUE;
3915: M->assembled = PETSC_FALSE;
3916: }
3917: MatGetOwnershipRange(M,&rstart,&rend);
3918: aij = (Mat_SeqAIJ*)(Mreuse)->data;
3919: ii = aij->i;
3920: jj = aij->j;
3921: aa = aij->a;
3922: for (i=0; i<m; i++) {
3923: row = rstart + i;
3924: nz = ii[i+1] - ii[i];
3925: cwork = jj; jj += nz;
3926: vwork = aa; aa += nz;
3927: MatSetValues_MPIAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);
3928: }
3930: MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);
3931: MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);
3932: *newmat = M;
3934: /* save submatrix used in processor for next request */
3935: if (call == MAT_INITIAL_MATRIX) {
3936: PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);
3937: MatDestroy(&Mreuse);
3938: }
3939: return(0);
3940: }
3942: PetscErrorCode MatMPIAIJSetPreallocationCSR_MPIAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[])
3943: {
3944: PetscInt m,cstart, cend,j,nnz,i,d;
3945: PetscInt *d_nnz,*o_nnz,nnz_max = 0,rstart,ii;
3946: const PetscInt *JJ;
3948: PetscBool nooffprocentries;
3951: if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Ii[0] must be 0 it is %D",Ii[0]);
3953: PetscLayoutSetUp(B->rmap);
3954: PetscLayoutSetUp(B->cmap);
3955: m = B->rmap->n;
3956: cstart = B->cmap->rstart;
3957: cend = B->cmap->rend;
3958: rstart = B->rmap->rstart;
3960: PetscCalloc2(m,&d_nnz,m,&o_nnz);
3962: #if defined(PETSC_USE_DEBUG)
3963: for (i=0; i<m; i++) {
3964: nnz = Ii[i+1]- Ii[i];
3965: JJ = J + Ii[i];
3966: if (nnz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative %D number of columns",i,nnz);
3967: if (nnz && (JJ[0] < 0)) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Row %D starts with negative column index",i,JJ[0]);
3968: 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);
3969: }
3970: #endif
3972: for (i=0; i<m; i++) {
3973: nnz = Ii[i+1]- Ii[i];
3974: JJ = J + Ii[i];
3975: nnz_max = PetscMax(nnz_max,nnz);
3976: d = 0;
3977: for (j=0; j<nnz; j++) {
3978: if (cstart <= JJ[j] && JJ[j] < cend) d++;
3979: }
3980: d_nnz[i] = d;
3981: o_nnz[i] = nnz - d;
3982: }
3983: MatMPIAIJSetPreallocation(B,0,d_nnz,0,o_nnz);
3984: PetscFree2(d_nnz,o_nnz);
3986: for (i=0; i<m; i++) {
3987: ii = i + rstart;
3988: MatSetValues_MPIAIJ(B,1,&ii,Ii[i+1] - Ii[i],J+Ii[i], v ? v + Ii[i] : NULL,INSERT_VALUES);
3989: }
3990: nooffprocentries = B->nooffprocentries;
3991: B->nooffprocentries = PETSC_TRUE;
3992: MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
3993: MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
3994: B->nooffprocentries = nooffprocentries;
3996: MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
3997: return(0);
3998: }
4000: /*@
4001: MatMPIAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in AIJ format
4002: (the default parallel PETSc format).
4004: Collective
4006: Input Parameters:
4007: + B - the matrix
4008: . i - the indices into j for the start of each local row (starts with zero)
4009: . j - the column indices for each local row (starts with zero)
4010: - v - optional values in the matrix
4012: Level: developer
4014: Notes:
4015: The i, j, and v arrays ARE copied by this routine into the internal format used by PETSc;
4016: thus you CANNOT change the matrix entries by changing the values of v[] after you have
4017: called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.
4019: The i and j indices are 0 based, and i indices are indices corresponding to the local j array.
4021: The format which is used for the sparse matrix input, is equivalent to a
4022: row-major ordering.. i.e for the following matrix, the input data expected is
4023: as shown
4025: $ 1 0 0
4026: $ 2 0 3 P0
4027: $ -------
4028: $ 4 5 6 P1
4029: $
4030: $ Process0 [P0]: rows_owned=[0,1]
4031: $ i = {0,1,3} [size = nrow+1 = 2+1]
4032: $ j = {0,0,2} [size = 3]
4033: $ v = {1,2,3} [size = 3]
4034: $
4035: $ Process1 [P1]: rows_owned=[2]
4036: $ i = {0,3} [size = nrow+1 = 1+1]
4037: $ j = {0,1,2} [size = 3]
4038: $ v = {4,5,6} [size = 3]
4040: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatCreateAIJ(), MATMPIAIJ,
4041: MatCreateSeqAIJWithArrays(), MatCreateMPIAIJWithSplitArrays()
4042: @*/
4043: PetscErrorCode MatMPIAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
4044: {
4048: PetscTryMethod(B,"MatMPIAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));
4049: return(0);
4050: }
4052: /*@C
4053: MatMPIAIJSetPreallocation - Preallocates memory for a sparse parallel matrix in AIJ format
4054: (the default parallel PETSc format). For good matrix assembly performance
4055: the user should preallocate the matrix storage by setting the parameters
4056: d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately,
4057: performance can be increased by more than a factor of 50.
4059: Collective
4061: Input Parameters:
4062: + B - the matrix
4063: . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix
4064: (same value is used for all local rows)
4065: . d_nnz - array containing the number of nonzeros in the various rows of the
4066: DIAGONAL portion of the local submatrix (possibly different for each row)
4067: or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure.
4068: The size of this array is equal to the number of local rows, i.e 'm'.
4069: For matrices that will be factored, you must leave room for (and set)
4070: the diagonal entry even if it is zero.
4071: . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local
4072: submatrix (same value is used for all local rows).
4073: - o_nnz - array containing the number of nonzeros in the various rows of the
4074: OFF-DIAGONAL portion of the local submatrix (possibly different for
4075: each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero
4076: structure. The size of this array is equal to the number
4077: of local rows, i.e 'm'.
4079: If the *_nnz parameter is given then the *_nz parameter is ignored
4081: The AIJ format (also called the Yale sparse matrix format or
4082: compressed row storage (CSR)), is fully compatible with standard Fortran 77
4083: storage. The stored row and column indices begin with zero.
4084: See Users-Manual: ch_mat for details.
4086: The parallel matrix is partitioned such that the first m0 rows belong to
4087: process 0, the next m1 rows belong to process 1, the next m2 rows belong
4088: to process 2 etc.. where m0,m1,m2... are the input parameter 'm'.
4090: The DIAGONAL portion of the local submatrix of a processor can be defined
4091: as the submatrix which is obtained by extraction the part corresponding to
4092: the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the
4093: first row that belongs to the processor, r2 is the last row belonging to
4094: the this processor, and c1-c2 is range of indices of the local part of a
4095: vector suitable for applying the matrix to. This is an mxn matrix. In the
4096: common case of a square matrix, the row and column ranges are the same and
4097: the DIAGONAL part is also square. The remaining portion of the local
4098: submatrix (mxN) constitute the OFF-DIAGONAL portion.
4100: If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.
4102: You can call MatGetInfo() to get information on how effective the preallocation was;
4103: for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
4104: You can also run with the option -info and look for messages with the string
4105: malloc in them to see if additional memory allocation was needed.
4107: Example usage:
4109: Consider the following 8x8 matrix with 34 non-zero values, that is
4110: assembled across 3 processors. Lets assume that proc0 owns 3 rows,
4111: proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown
4112: as follows:
4114: .vb
4115: 1 2 0 | 0 3 0 | 0 4
4116: Proc0 0 5 6 | 7 0 0 | 8 0
4117: 9 0 10 | 11 0 0 | 12 0
4118: -------------------------------------
4119: 13 0 14 | 15 16 17 | 0 0
4120: Proc1 0 18 0 | 19 20 21 | 0 0
4121: 0 0 0 | 22 23 0 | 24 0
4122: -------------------------------------
4123: Proc2 25 26 27 | 0 0 28 | 29 0
4124: 30 0 0 | 31 32 33 | 0 34
4125: .ve
4127: This can be represented as a collection of submatrices as:
4129: .vb
4130: A B C
4131: D E F
4132: G H I
4133: .ve
4135: Where the submatrices A,B,C are owned by proc0, D,E,F are
4136: owned by proc1, G,H,I are owned by proc2.
4138: The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
4139: The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
4140: The 'M','N' parameters are 8,8, and have the same values on all procs.
4142: The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
4143: submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
4144: corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
4145: Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
4146: part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ
4147: matrix, ans [DF] as another SeqAIJ matrix.
4149: When d_nz, o_nz parameters are specified, d_nz storage elements are
4150: allocated for every row of the local diagonal submatrix, and o_nz
4151: storage locations are allocated for every row of the OFF-DIAGONAL submat.
4152: One way to choose d_nz and o_nz is to use the max nonzerors per local
4153: rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices.
4154: In this case, the values of d_nz,o_nz are:
4155: .vb
4156: proc0 : dnz = 2, o_nz = 2
4157: proc1 : dnz = 3, o_nz = 2
4158: proc2 : dnz = 1, o_nz = 4
4159: .ve
4160: We are allocating m*(d_nz+o_nz) storage locations for every proc. This
4161: translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
4162: for proc3. i.e we are using 12+15+10=37 storage locations to store
4163: 34 values.
4165: When d_nnz, o_nnz parameters are specified, the storage is specified
4166: for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
4167: In the above case the values for d_nnz,o_nnz are:
4168: .vb
4169: proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
4170: proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
4171: proc2: d_nnz = [1,1] and o_nnz = [4,4]
4172: .ve
4173: Here the space allocated is sum of all the above values i.e 34, and
4174: hence pre-allocation is perfect.
4176: Level: intermediate
4178: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateAIJ(), MatMPIAIJSetPreallocationCSR(),
4179: MATMPIAIJ, MatGetInfo(), PetscSplitOwnership()
4180: @*/
4181: PetscErrorCode MatMPIAIJSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
4182: {
4188: PetscTryMethod(B,"MatMPIAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));
4189: return(0);
4190: }
4192: /*@
4193: MatCreateMPIAIJWithArrays - creates a MPI AIJ matrix using arrays that contain in standard
4194: CSR format for the local rows.
4196: Collective
4198: Input Parameters:
4199: + comm - MPI communicator
4200: . m - number of local rows (Cannot be PETSC_DECIDE)
4201: . n - This value should be the same as the local size used in creating the
4202: x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
4203: calculated if N is given) For square matrices n is almost always m.
4204: . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
4205: . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
4206: . i - row indices; that is i[0] = 0, i[row] = i[row-1] + number of elements in that row of the matrix
4207: . j - column indices
4208: - a - matrix values
4210: Output Parameter:
4211: . mat - the matrix
4213: Level: intermediate
4215: Notes:
4216: The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
4217: thus you CANNOT change the matrix entries by changing the values of a[] after you have
4218: called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.
4220: The i and j indices are 0 based, and i indices are indices corresponding to the local j array.
4222: The format which is used for the sparse matrix input, is equivalent to a
4223: row-major ordering.. i.e for the following matrix, the input data expected is
4224: as shown
4226: Once you have created the matrix you can update it with new numerical values using MatUpdateMPIAIJWithArrays
4228: $ 1 0 0
4229: $ 2 0 3 P0
4230: $ -------
4231: $ 4 5 6 P1
4232: $
4233: $ Process0 [P0]: rows_owned=[0,1]
4234: $ i = {0,1,3} [size = nrow+1 = 2+1]
4235: $ j = {0,0,2} [size = 3]
4236: $ v = {1,2,3} [size = 3]
4237: $
4238: $ Process1 [P1]: rows_owned=[2]
4239: $ i = {0,3} [size = nrow+1 = 1+1]
4240: $ j = {0,1,2} [size = 3]
4241: $ v = {4,5,6} [size = 3]
4243: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
4244: MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays(), MatUpdateMPIAIJWithArrays()
4245: @*/
4246: PetscErrorCode MatCreateMPIAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat)
4247: {
4251: if (i && i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
4252: if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
4253: MatCreate(comm,mat);
4254: MatSetSizes(*mat,m,n,M,N);
4255: /* MatSetBlockSizes(M,bs,cbs); */
4256: MatSetType(*mat,MATMPIAIJ);
4257: MatMPIAIJSetPreallocationCSR(*mat,i,j,a);
4258: return(0);
4259: }
4261: /*@
4262: MatUpdateMPIAIJWithArrays - updates a MPI AIJ matrix using arrays that contain in standard
4263: CSR format for the local rows. Only the numerical values are updated the other arrays must be identical
4265: Collective
4267: Input Parameters:
4268: + mat - the matrix
4269: . m - number of local rows (Cannot be PETSC_DECIDE)
4270: . n - This value should be the same as the local size used in creating the
4271: x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
4272: calculated if N is given) For square matrices n is almost always m.
4273: . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
4274: . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
4275: . Ii - row indices; that is Ii[0] = 0, Ii[row] = Ii[row-1] + number of elements in that row of the matrix
4276: . J - column indices
4277: - v - matrix values
4279: Level: intermediate
4281: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
4282: MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays(), MatUpdateMPIAIJWithArrays()
4283: @*/
4284: PetscErrorCode MatUpdateMPIAIJWithArrays(Mat mat,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[])
4285: {
4287: PetscInt cstart,nnz,i,j;
4288: PetscInt *ld;
4289: PetscBool nooffprocentries;
4290: Mat_MPIAIJ *Aij = (Mat_MPIAIJ*)mat->data;
4291: Mat_SeqAIJ *Ad = (Mat_SeqAIJ*)Aij->A->data, *Ao = (Mat_SeqAIJ*)Aij->B->data;
4292: PetscScalar *ad = Ad->a, *ao = Ao->a;
4293: const PetscInt *Adi = Ad->i;
4294: PetscInt ldi,Iii,md;
4297: if (Ii[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
4298: if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
4299: if (m != mat->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Local number of rows cannot change from call to MatUpdateMPIAIJWithArrays()");
4300: if (n != mat->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Local number of columns cannot change from call to MatUpdateMPIAIJWithArrays()");
4302: cstart = mat->cmap->rstart;
4303: if (!Aij->ld) {
4304: /* count number of entries below block diagonal */
4305: PetscCalloc1(m,&ld);
4306: Aij->ld = ld;
4307: for (i=0; i<m; i++) {
4308: nnz = Ii[i+1]- Ii[i];
4309: j = 0;
4310: while (J[j] < cstart && j < nnz) {j++;}
4311: J += nnz;
4312: ld[i] = j;
4313: }
4314: } else {
4315: ld = Aij->ld;
4316: }
4318: for (i=0; i<m; i++) {
4319: nnz = Ii[i+1]- Ii[i];
4320: Iii = Ii[i];
4321: ldi = ld[i];
4322: md = Adi[i+1]-Adi[i];
4323: PetscArraycpy(ao,v + Iii,ldi);
4324: PetscArraycpy(ad,v + Iii + ldi,md);
4325: PetscArraycpy(ao + ldi,v + Iii + ldi + md,nnz - ldi - md);
4326: ad += md;
4327: ao += nnz - md;
4328: }
4329: nooffprocentries = mat->nooffprocentries;
4330: mat->nooffprocentries = PETSC_TRUE;
4331: PetscObjectStateIncrease((PetscObject)Aij->A);
4332: PetscObjectStateIncrease((PetscObject)Aij->B);
4333: PetscObjectStateIncrease((PetscObject)mat);
4334: MatAssemblyBegin(mat,MAT_FINAL_ASSEMBLY);
4335: MatAssemblyEnd(mat,MAT_FINAL_ASSEMBLY);
4336: mat->nooffprocentries = nooffprocentries;
4337: return(0);
4338: }
4340: /*@C
4341: MatCreateAIJ - Creates a sparse parallel matrix in AIJ format
4342: (the default parallel PETSc format). For good matrix assembly performance
4343: the user should preallocate the matrix storage by setting the parameters
4344: d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately,
4345: performance can be increased by more than a factor of 50.
4347: Collective
4349: Input Parameters:
4350: + comm - MPI communicator
4351: . m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
4352: This value should be the same as the local size used in creating the
4353: y vector for the matrix-vector product y = Ax.
4354: . n - This value should be the same as the local size used in creating the
4355: x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
4356: calculated if N is given) For square matrices n is almost always m.
4357: . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
4358: . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
4359: . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix
4360: (same value is used for all local rows)
4361: . d_nnz - array containing the number of nonzeros in the various rows of the
4362: DIAGONAL portion of the local submatrix (possibly different for each row)
4363: or NULL, if d_nz is used to specify the nonzero structure.
4364: The size of this array is equal to the number of local rows, i.e 'm'.
4365: . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local
4366: submatrix (same value is used for all local rows).
4367: - o_nnz - array containing the number of nonzeros in the various rows of the
4368: OFF-DIAGONAL portion of the local submatrix (possibly different for
4369: each row) or NULL, if o_nz is used to specify the nonzero
4370: structure. The size of this array is equal to the number
4371: of local rows, i.e 'm'.
4373: Output Parameter:
4374: . A - the matrix
4376: It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
4377: MatXXXXSetPreallocation() paradigm instead of this routine directly.
4378: [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]
4380: Notes:
4381: If the *_nnz parameter is given then the *_nz parameter is ignored
4383: m,n,M,N parameters specify the size of the matrix, and its partitioning across
4384: processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate
4385: storage requirements for this matrix.
4387: If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one
4388: processor than it must be used on all processors that share the object for
4389: that argument.
4391: The user MUST specify either the local or global matrix dimensions
4392: (possibly both).
4394: The parallel matrix is partitioned across processors such that the
4395: first m0 rows belong to process 0, the next m1 rows belong to
4396: process 1, the next m2 rows belong to process 2 etc.. where
4397: m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores
4398: values corresponding to [m x N] submatrix.
4400: The columns are logically partitioned with the n0 columns belonging
4401: to 0th partition, the next n1 columns belonging to the next
4402: partition etc.. where n0,n1,n2... are the input parameter 'n'.
4404: The DIAGONAL portion of the local submatrix on any given processor
4405: is the submatrix corresponding to the rows and columns m,n
4406: corresponding to the given processor. i.e diagonal matrix on
4407: process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1]
4408: etc. The remaining portion of the local submatrix [m x (N-n)]
4409: constitute the OFF-DIAGONAL portion. The example below better
4410: illustrates this concept.
4412: For a square global matrix we define each processor's diagonal portion
4413: to be its local rows and the corresponding columns (a square submatrix);
4414: each processor's off-diagonal portion encompasses the remainder of the
4415: local matrix (a rectangular submatrix).
4417: If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.
4419: When calling this routine with a single process communicator, a matrix of
4420: type SEQAIJ is returned. If a matrix of type MPIAIJ is desired for this
4421: type of communicator, use the construction mechanism
4422: .vb
4423: MatCreate(...,&A); MatSetType(A,MATMPIAIJ); MatSetSizes(A, m,n,M,N); MatMPIAIJSetPreallocation(A,...);
4424: .ve
4426: $ MatCreate(...,&A);
4427: $ MatSetType(A,MATMPIAIJ);
4428: $ MatSetSizes(A, m,n,M,N);
4429: $ MatMPIAIJSetPreallocation(A,...);
4431: By default, this format uses inodes (identical nodes) when possible.
4432: We search for consecutive rows with the same nonzero structure, thereby
4433: reusing matrix information to achieve increased efficiency.
4435: Options Database Keys:
4436: + -mat_no_inode - Do not use inodes
4437: - -mat_inode_limit <limit> - Sets inode limit (max limit=5)
4441: Example usage:
4443: Consider the following 8x8 matrix with 34 non-zero values, that is
4444: assembled across 3 processors. Lets assume that proc0 owns 3 rows,
4445: proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown
4446: as follows
4448: .vb
4449: 1 2 0 | 0 3 0 | 0 4
4450: Proc0 0 5 6 | 7 0 0 | 8 0
4451: 9 0 10 | 11 0 0 | 12 0
4452: -------------------------------------
4453: 13 0 14 | 15 16 17 | 0 0
4454: Proc1 0 18 0 | 19 20 21 | 0 0
4455: 0 0 0 | 22 23 0 | 24 0
4456: -------------------------------------
4457: Proc2 25 26 27 | 0 0 28 | 29 0
4458: 30 0 0 | 31 32 33 | 0 34
4459: .ve
4461: This can be represented as a collection of submatrices as
4463: .vb
4464: A B C
4465: D E F
4466: G H I
4467: .ve
4469: Where the submatrices A,B,C are owned by proc0, D,E,F are
4470: owned by proc1, G,H,I are owned by proc2.
4472: The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
4473: The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
4474: The 'M','N' parameters are 8,8, and have the same values on all procs.
4476: The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
4477: submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
4478: corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
4479: Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
4480: part as SeqAIJ matrices. for eg: proc1 will store [E] as a SeqAIJ
4481: matrix, ans [DF] as another SeqAIJ matrix.
4483: When d_nz, o_nz parameters are specified, d_nz storage elements are
4484: allocated for every row of the local diagonal submatrix, and o_nz
4485: storage locations are allocated for every row of the OFF-DIAGONAL submat.
4486: One way to choose d_nz and o_nz is to use the max nonzerors per local
4487: rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices.
4488: In this case, the values of d_nz,o_nz are
4489: .vb
4490: proc0 : dnz = 2, o_nz = 2
4491: proc1 : dnz = 3, o_nz = 2
4492: proc2 : dnz = 1, o_nz = 4
4493: .ve
4494: We are allocating m*(d_nz+o_nz) storage locations for every proc. This
4495: translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
4496: for proc3. i.e we are using 12+15+10=37 storage locations to store
4497: 34 values.
4499: When d_nnz, o_nnz parameters are specified, the storage is specified
4500: for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
4501: In the above case the values for d_nnz,o_nnz are
4502: .vb
4503: proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
4504: proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
4505: proc2: d_nnz = [1,1] and o_nnz = [4,4]
4506: .ve
4507: Here the space allocated is sum of all the above values i.e 34, and
4508: hence pre-allocation is perfect.
4510: Level: intermediate
4512: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
4513: MATMPIAIJ, MatCreateMPIAIJWithArrays()
4514: @*/
4515: 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)
4516: {
4518: PetscMPIInt size;
4521: MatCreate(comm,A);
4522: MatSetSizes(*A,m,n,M,N);
4523: MPI_Comm_size(comm,&size);
4524: if (size > 1) {
4525: MatSetType(*A,MATMPIAIJ);
4526: MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);
4527: } else {
4528: MatSetType(*A,MATSEQAIJ);
4529: MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);
4530: }
4531: return(0);
4532: }
4534: PetscErrorCode MatMPIAIJGetSeqAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[])
4535: {
4536: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
4537: PetscBool flg;
4541: PetscStrbeginswith(((PetscObject)A)->type_name,MATMPIAIJ,&flg);
4542: if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"This function requires a MATMPIAIJ matrix as input");
4543: if (Ad) *Ad = a->A;
4544: if (Ao) *Ao = a->B;
4545: if (colmap) *colmap = a->garray;
4546: return(0);
4547: }
4549: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
4550: {
4552: PetscInt m,N,i,rstart,nnz,Ii;
4553: PetscInt *indx;
4554: PetscScalar *values;
4557: MatGetSize(inmat,&m,&N);
4558: if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */
4559: PetscInt *dnz,*onz,sum,bs,cbs;
4561: if (n == PETSC_DECIDE) {
4562: PetscSplitOwnership(comm,&n,&N);
4563: }
4564: /* Check sum(n) = N */
4565: MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);
4566: if (sum != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns %D != global columns %D",sum,N);
4568: MPI_Scan(&m, &rstart,1,MPIU_INT,MPI_SUM,comm);
4569: rstart -= m;
4571: MatPreallocateInitialize(comm,m,n,dnz,onz);
4572: for (i=0; i<m; i++) {
4573: MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);
4574: MatPreallocateSet(i+rstart,nnz,indx,dnz,onz);
4575: MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,NULL);
4576: }
4578: MatCreate(comm,outmat);
4579: MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
4580: MatGetBlockSizes(inmat,&bs,&cbs);
4581: MatSetBlockSizes(*outmat,bs,cbs);
4582: MatSetType(*outmat,MATAIJ);
4583: MatSeqAIJSetPreallocation(*outmat,0,dnz);
4584: MatMPIAIJSetPreallocation(*outmat,0,dnz,0,onz);
4585: MatPreallocateFinalize(dnz,onz);
4586: }
4588: /* numeric phase */
4589: MatGetOwnershipRange(*outmat,&rstart,NULL);
4590: for (i=0; i<m; i++) {
4591: MatGetRow_SeqAIJ(inmat,i,&nnz,&indx,&values);
4592: Ii = i + rstart;
4593: MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);
4594: MatRestoreRow_SeqAIJ(inmat,i,&nnz,&indx,&values);
4595: }
4596: MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);
4597: MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);
4598: return(0);
4599: }
4601: PetscErrorCode MatFileSplit(Mat A,char *outfile)
4602: {
4603: PetscErrorCode ierr;
4604: PetscMPIInt rank;
4605: PetscInt m,N,i,rstart,nnz;
4606: size_t len;
4607: const PetscInt *indx;
4608: PetscViewer out;
4609: char *name;
4610: Mat B;
4611: const PetscScalar *values;
4614: MatGetLocalSize(A,&m,0);
4615: MatGetSize(A,0,&N);
4616: /* Should this be the type of the diagonal block of A? */
4617: MatCreate(PETSC_COMM_SELF,&B);
4618: MatSetSizes(B,m,N,m,N);
4619: MatSetBlockSizesFromMats(B,A,A);
4620: MatSetType(B,MATSEQAIJ);
4621: MatSeqAIJSetPreallocation(B,0,NULL);
4622: MatGetOwnershipRange(A,&rstart,0);
4623: for (i=0; i<m; i++) {
4624: MatGetRow(A,i+rstart,&nnz,&indx,&values);
4625: MatSetValues(B,1,&i,nnz,indx,values,INSERT_VALUES);
4626: MatRestoreRow(A,i+rstart,&nnz,&indx,&values);
4627: }
4628: MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
4629: MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
4631: MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);
4632: PetscStrlen(outfile,&len);
4633: PetscMalloc1(len+5,&name);
4634: sprintf(name,"%s.%d",outfile,rank);
4635: PetscViewerBinaryOpen(PETSC_COMM_SELF,name,FILE_MODE_APPEND,&out);
4636: PetscFree(name);
4637: MatView(B,out);
4638: PetscViewerDestroy(&out);
4639: MatDestroy(&B);
4640: return(0);
4641: }
4643: PetscErrorCode MatDestroy_MPIAIJ_SeqsToMPI(Mat A)
4644: {
4645: PetscErrorCode ierr;
4646: Mat_Merge_SeqsToMPI *merge;
4647: PetscContainer container;
4650: PetscObjectQuery((PetscObject)A,"MatMergeSeqsToMPI",(PetscObject*)&container);
4651: if (container) {
4652: PetscContainerGetPointer(container,(void**)&merge);
4653: PetscFree(merge->id_r);
4654: PetscFree(merge->len_s);
4655: PetscFree(merge->len_r);
4656: PetscFree(merge->bi);
4657: PetscFree(merge->bj);
4658: PetscFree(merge->buf_ri[0]);
4659: PetscFree(merge->buf_ri);
4660: PetscFree(merge->buf_rj[0]);
4661: PetscFree(merge->buf_rj);
4662: PetscFree(merge->coi);
4663: PetscFree(merge->coj);
4664: PetscFree(merge->owners_co);
4665: PetscLayoutDestroy(&merge->rowmap);
4666: PetscFree(merge);
4667: PetscObjectCompose((PetscObject)A,"MatMergeSeqsToMPI",0);
4668: }
4669: MatDestroy_MPIAIJ(A);
4670: return(0);
4671: }
4673: #include <../src/mat/utils/freespace.h>
4674: #include <petscbt.h>
4676: PetscErrorCode MatCreateMPIAIJSumSeqAIJNumeric(Mat seqmat,Mat mpimat)
4677: {
4678: PetscErrorCode ierr;
4679: MPI_Comm comm;
4680: Mat_SeqAIJ *a =(Mat_SeqAIJ*)seqmat->data;
4681: PetscMPIInt size,rank,taga,*len_s;
4682: PetscInt N=mpimat->cmap->N,i,j,*owners,*ai=a->i,*aj;
4683: PetscInt proc,m;
4684: PetscInt **buf_ri,**buf_rj;
4685: PetscInt k,anzi,*bj_i,*bi,*bj,arow,bnzi,nextaj;
4686: PetscInt nrows,**buf_ri_k,**nextrow,**nextai;
4687: MPI_Request *s_waits,*r_waits;
4688: MPI_Status *status;
4689: MatScalar *aa=a->a;
4690: MatScalar **abuf_r,*ba_i;
4691: Mat_Merge_SeqsToMPI *merge;
4692: PetscContainer container;
4695: PetscObjectGetComm((PetscObject)mpimat,&comm);
4696: PetscLogEventBegin(MAT_Seqstompinum,seqmat,0,0,0);
4698: MPI_Comm_size(comm,&size);
4699: MPI_Comm_rank(comm,&rank);
4701: PetscObjectQuery((PetscObject)mpimat,"MatMergeSeqsToMPI",(PetscObject*)&container);
4702: PetscContainerGetPointer(container,(void**)&merge);
4704: bi = merge->bi;
4705: bj = merge->bj;
4706: buf_ri = merge->buf_ri;
4707: buf_rj = merge->buf_rj;
4709: PetscMalloc1(size,&status);
4710: owners = merge->rowmap->range;
4711: len_s = merge->len_s;
4713: /* send and recv matrix values */
4714: /*-----------------------------*/
4715: PetscObjectGetNewTag((PetscObject)mpimat,&taga);
4716: PetscPostIrecvScalar(comm,taga,merge->nrecv,merge->id_r,merge->len_r,&abuf_r,&r_waits);
4718: PetscMalloc1(merge->nsend+1,&s_waits);
4719: for (proc=0,k=0; proc<size; proc++) {
4720: if (!len_s[proc]) continue;
4721: i = owners[proc];
4722: MPI_Isend(aa+ai[i],len_s[proc],MPIU_MATSCALAR,proc,taga,comm,s_waits+k);
4723: k++;
4724: }
4726: if (merge->nrecv) {MPI_Waitall(merge->nrecv,r_waits,status);}
4727: if (merge->nsend) {MPI_Waitall(merge->nsend,s_waits,status);}
4728: PetscFree(status);
4730: PetscFree(s_waits);
4731: PetscFree(r_waits);
4733: /* insert mat values of mpimat */
4734: /*----------------------------*/
4735: PetscMalloc1(N,&ba_i);
4736: PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);
4738: for (k=0; k<merge->nrecv; k++) {
4739: buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */
4740: nrows = *(buf_ri_k[k]);
4741: nextrow[k] = buf_ri_k[k]+1; /* next row number of k-th recved i-structure */
4742: nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */
4743: }
4745: /* set values of ba */
4746: m = merge->rowmap->n;
4747: for (i=0; i<m; i++) {
4748: arow = owners[rank] + i;
4749: bj_i = bj+bi[i]; /* col indices of the i-th row of mpimat */
4750: bnzi = bi[i+1] - bi[i];
4751: PetscArrayzero(ba_i,bnzi);
4753: /* add local non-zero vals of this proc's seqmat into ba */
4754: anzi = ai[arow+1] - ai[arow];
4755: aj = a->j + ai[arow];
4756: aa = a->a + ai[arow];
4757: nextaj = 0;
4758: for (j=0; nextaj<anzi; j++) {
4759: if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */
4760: ba_i[j] += aa[nextaj++];
4761: }
4762: }
4764: /* add received vals into ba */
4765: for (k=0; k<merge->nrecv; k++) { /* k-th received message */
4766: /* i-th row */
4767: if (i == *nextrow[k]) {
4768: anzi = *(nextai[k]+1) - *nextai[k];
4769: aj = buf_rj[k] + *(nextai[k]);
4770: aa = abuf_r[k] + *(nextai[k]);
4771: nextaj = 0;
4772: for (j=0; nextaj<anzi; j++) {
4773: if (*(bj_i + j) == aj[nextaj]) { /* bcol == acol */
4774: ba_i[j] += aa[nextaj++];
4775: }
4776: }
4777: nextrow[k]++; nextai[k]++;
4778: }
4779: }
4780: MatSetValues(mpimat,1,&arow,bnzi,bj_i,ba_i,INSERT_VALUES);
4781: }
4782: MatAssemblyBegin(mpimat,MAT_FINAL_ASSEMBLY);
4783: MatAssemblyEnd(mpimat,MAT_FINAL_ASSEMBLY);
4785: PetscFree(abuf_r[0]);
4786: PetscFree(abuf_r);
4787: PetscFree(ba_i);
4788: PetscFree3(buf_ri_k,nextrow,nextai);
4789: PetscLogEventEnd(MAT_Seqstompinum,seqmat,0,0,0);
4790: return(0);
4791: }
4793: PetscErrorCode MatCreateMPIAIJSumSeqAIJSymbolic(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,Mat *mpimat)
4794: {
4795: PetscErrorCode ierr;
4796: Mat B_mpi;
4797: Mat_SeqAIJ *a=(Mat_SeqAIJ*)seqmat->data;
4798: PetscMPIInt size,rank,tagi,tagj,*len_s,*len_si,*len_ri;
4799: PetscInt **buf_rj,**buf_ri,**buf_ri_k;
4800: PetscInt M=seqmat->rmap->n,N=seqmat->cmap->n,i,*owners,*ai=a->i,*aj=a->j;
4801: PetscInt len,proc,*dnz,*onz,bs,cbs;
4802: PetscInt k,anzi,*bi,*bj,*lnk,nlnk,arow,bnzi,nspacedouble=0;
4803: PetscInt nrows,*buf_s,*buf_si,*buf_si_i,**nextrow,**nextai;
4804: MPI_Request *si_waits,*sj_waits,*ri_waits,*rj_waits;
4805: MPI_Status *status;
4806: PetscFreeSpaceList free_space=NULL,current_space=NULL;
4807: PetscBT lnkbt;
4808: Mat_Merge_SeqsToMPI *merge;
4809: PetscContainer container;
4812: PetscLogEventBegin(MAT_Seqstompisym,seqmat,0,0,0);
4814: /* make sure it is a PETSc comm */
4815: PetscCommDuplicate(comm,&comm,NULL);
4816: MPI_Comm_size(comm,&size);
4817: MPI_Comm_rank(comm,&rank);
4819: PetscNew(&merge);
4820: PetscMalloc1(size,&status);
4822: /* determine row ownership */
4823: /*---------------------------------------------------------*/
4824: PetscLayoutCreate(comm,&merge->rowmap);
4825: PetscLayoutSetLocalSize(merge->rowmap,m);
4826: PetscLayoutSetSize(merge->rowmap,M);
4827: PetscLayoutSetBlockSize(merge->rowmap,1);
4828: PetscLayoutSetUp(merge->rowmap);
4829: PetscMalloc1(size,&len_si);
4830: PetscMalloc1(size,&merge->len_s);
4832: m = merge->rowmap->n;
4833: owners = merge->rowmap->range;
4835: /* determine the number of messages to send, their lengths */
4836: /*---------------------------------------------------------*/
4837: len_s = merge->len_s;
4839: len = 0; /* length of buf_si[] */
4840: merge->nsend = 0;
4841: for (proc=0; proc<size; proc++) {
4842: len_si[proc] = 0;
4843: if (proc == rank) {
4844: len_s[proc] = 0;
4845: } else {
4846: len_si[proc] = owners[proc+1] - owners[proc] + 1;
4847: len_s[proc] = ai[owners[proc+1]] - ai[owners[proc]]; /* num of rows to be sent to [proc] */
4848: }
4849: if (len_s[proc]) {
4850: merge->nsend++;
4851: nrows = 0;
4852: for (i=owners[proc]; i<owners[proc+1]; i++) {
4853: if (ai[i+1] > ai[i]) nrows++;
4854: }
4855: len_si[proc] = 2*(nrows+1);
4856: len += len_si[proc];
4857: }
4858: }
4860: /* determine the number and length of messages to receive for ij-structure */
4861: /*-------------------------------------------------------------------------*/
4862: PetscGatherNumberOfMessages(comm,NULL,len_s,&merge->nrecv);
4863: PetscGatherMessageLengths2(comm,merge->nsend,merge->nrecv,len_s,len_si,&merge->id_r,&merge->len_r,&len_ri);
4865: /* post the Irecv of j-structure */
4866: /*-------------------------------*/
4867: PetscCommGetNewTag(comm,&tagj);
4868: PetscPostIrecvInt(comm,tagj,merge->nrecv,merge->id_r,merge->len_r,&buf_rj,&rj_waits);
4870: /* post the Isend of j-structure */
4871: /*--------------------------------*/
4872: PetscMalloc2(merge->nsend,&si_waits,merge->nsend,&sj_waits);
4874: for (proc=0, k=0; proc<size; proc++) {
4875: if (!len_s[proc]) continue;
4876: i = owners[proc];
4877: MPI_Isend(aj+ai[i],len_s[proc],MPIU_INT,proc,tagj,comm,sj_waits+k);
4878: k++;
4879: }
4881: /* receives and sends of j-structure are complete */
4882: /*------------------------------------------------*/
4883: if (merge->nrecv) {MPI_Waitall(merge->nrecv,rj_waits,status);}
4884: if (merge->nsend) {MPI_Waitall(merge->nsend,sj_waits,status);}
4886: /* send and recv i-structure */
4887: /*---------------------------*/
4888: PetscCommGetNewTag(comm,&tagi);
4889: PetscPostIrecvInt(comm,tagi,merge->nrecv,merge->id_r,len_ri,&buf_ri,&ri_waits);
4891: PetscMalloc1(len+1,&buf_s);
4892: buf_si = buf_s; /* points to the beginning of k-th msg to be sent */
4893: for (proc=0,k=0; proc<size; proc++) {
4894: if (!len_s[proc]) continue;
4895: /* form outgoing message for i-structure:
4896: buf_si[0]: nrows to be sent
4897: [1:nrows]: row index (global)
4898: [nrows+1:2*nrows+1]: i-structure index
4899: */
4900: /*-------------------------------------------*/
4901: nrows = len_si[proc]/2 - 1;
4902: buf_si_i = buf_si + nrows+1;
4903: buf_si[0] = nrows;
4904: buf_si_i[0] = 0;
4905: nrows = 0;
4906: for (i=owners[proc]; i<owners[proc+1]; i++) {
4907: anzi = ai[i+1] - ai[i];
4908: if (anzi) {
4909: buf_si_i[nrows+1] = buf_si_i[nrows] + anzi; /* i-structure */
4910: buf_si[nrows+1] = i-owners[proc]; /* local row index */
4911: nrows++;
4912: }
4913: }
4914: MPI_Isend(buf_si,len_si[proc],MPIU_INT,proc,tagi,comm,si_waits+k);
4915: k++;
4916: buf_si += len_si[proc];
4917: }
4919: if (merge->nrecv) {MPI_Waitall(merge->nrecv,ri_waits,status);}
4920: if (merge->nsend) {MPI_Waitall(merge->nsend,si_waits,status);}
4922: PetscInfo2(seqmat,"nsend: %D, nrecv: %D\n",merge->nsend,merge->nrecv);
4923: for (i=0; i<merge->nrecv; i++) {
4924: PetscInfo3(seqmat,"recv len_ri=%D, len_rj=%D from [%D]\n",len_ri[i],merge->len_r[i],merge->id_r[i]);
4925: }
4927: PetscFree(len_si);
4928: PetscFree(len_ri);
4929: PetscFree(rj_waits);
4930: PetscFree2(si_waits,sj_waits);
4931: PetscFree(ri_waits);
4932: PetscFree(buf_s);
4933: PetscFree(status);
4935: /* compute a local seq matrix in each processor */
4936: /*----------------------------------------------*/
4937: /* allocate bi array and free space for accumulating nonzero column info */
4938: PetscMalloc1(m+1,&bi);
4939: bi[0] = 0;
4941: /* create and initialize a linked list */
4942: nlnk = N+1;
4943: PetscLLCreate(N,N,nlnk,lnk,lnkbt);
4945: /* initial FreeSpace size is 2*(num of local nnz(seqmat)) */
4946: len = ai[owners[rank+1]] - ai[owners[rank]];
4947: PetscFreeSpaceGet(PetscIntMultTruncate(2,len)+1,&free_space);
4949: current_space = free_space;
4951: /* determine symbolic info for each local row */
4952: PetscMalloc3(merge->nrecv,&buf_ri_k,merge->nrecv,&nextrow,merge->nrecv,&nextai);
4954: for (k=0; k<merge->nrecv; k++) {
4955: buf_ri_k[k] = buf_ri[k]; /* beginning of k-th recved i-structure */
4956: nrows = *buf_ri_k[k];
4957: nextrow[k] = buf_ri_k[k] + 1; /* next row number of k-th recved i-structure */
4958: nextai[k] = buf_ri_k[k] + (nrows + 1); /* poins to the next i-structure of k-th recved i-structure */
4959: }
4961: MatPreallocateInitialize(comm,m,n,dnz,onz);
4962: len = 0;
4963: for (i=0; i<m; i++) {
4964: bnzi = 0;
4965: /* add local non-zero cols of this proc's seqmat into lnk */
4966: arow = owners[rank] + i;
4967: anzi = ai[arow+1] - ai[arow];
4968: aj = a->j + ai[arow];
4969: PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);
4970: bnzi += nlnk;
4971: /* add received col data into lnk */
4972: for (k=0; k<merge->nrecv; k++) { /* k-th received message */
4973: if (i == *nextrow[k]) { /* i-th row */
4974: anzi = *(nextai[k]+1) - *nextai[k];
4975: aj = buf_rj[k] + *nextai[k];
4976: PetscLLAddSorted(anzi,aj,N,nlnk,lnk,lnkbt);
4977: bnzi += nlnk;
4978: nextrow[k]++; nextai[k]++;
4979: }
4980: }
4981: if (len < bnzi) len = bnzi; /* =max(bnzi) */
4983: /* if free space is not available, make more free space */
4984: if (current_space->local_remaining<bnzi) {
4985: PetscFreeSpaceGet(PetscIntSumTruncate(bnzi,current_space->total_array_size),¤t_space);
4986: nspacedouble++;
4987: }
4988: /* copy data into free space, then initialize lnk */
4989: PetscLLClean(N,N,bnzi,lnk,current_space->array,lnkbt);
4990: MatPreallocateSet(i+owners[rank],bnzi,current_space->array,dnz,onz);
4992: current_space->array += bnzi;
4993: current_space->local_used += bnzi;
4994: current_space->local_remaining -= bnzi;
4996: bi[i+1] = bi[i] + bnzi;
4997: }
4999: PetscFree3(buf_ri_k,nextrow,nextai);
5001: PetscMalloc1(bi[m]+1,&bj);
5002: PetscFreeSpaceContiguous(&free_space,bj);
5003: PetscLLDestroy(lnk,lnkbt);
5005: /* create symbolic parallel matrix B_mpi */
5006: /*---------------------------------------*/
5007: MatGetBlockSizes(seqmat,&bs,&cbs);
5008: MatCreate(comm,&B_mpi);
5009: if (n==PETSC_DECIDE) {
5010: MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,N);
5011: } else {
5012: MatSetSizes(B_mpi,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
5013: }
5014: MatSetBlockSizes(B_mpi,bs,cbs);
5015: MatSetType(B_mpi,MATMPIAIJ);
5016: MatMPIAIJSetPreallocation(B_mpi,0,dnz,0,onz);
5017: MatPreallocateFinalize(dnz,onz);
5018: MatSetOption(B_mpi,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_FALSE);
5020: /* B_mpi is not ready for use - assembly will be done by MatCreateMPIAIJSumSeqAIJNumeric() */
5021: B_mpi->assembled = PETSC_FALSE;
5022: B_mpi->ops->destroy = MatDestroy_MPIAIJ_SeqsToMPI;
5023: merge->bi = bi;
5024: merge->bj = bj;
5025: merge->buf_ri = buf_ri;
5026: merge->buf_rj = buf_rj;
5027: merge->coi = NULL;
5028: merge->coj = NULL;
5029: merge->owners_co = NULL;
5031: PetscCommDestroy(&comm);
5033: /* attach the supporting struct to B_mpi for reuse */
5034: PetscContainerCreate(PETSC_COMM_SELF,&container);
5035: PetscContainerSetPointer(container,merge);
5036: PetscObjectCompose((PetscObject)B_mpi,"MatMergeSeqsToMPI",(PetscObject)container);
5037: PetscContainerDestroy(&container);
5038: *mpimat = B_mpi;
5040: PetscLogEventEnd(MAT_Seqstompisym,seqmat,0,0,0);
5041: return(0);
5042: }
5044: /*@C
5045: MatCreateMPIAIJSumSeqAIJ - Creates a MATMPIAIJ matrix by adding sequential
5046: matrices from each processor
5048: Collective
5050: Input Parameters:
5051: + comm - the communicators the parallel matrix will live on
5052: . seqmat - the input sequential matrices
5053: . m - number of local rows (or PETSC_DECIDE)
5054: . n - number of local columns (or PETSC_DECIDE)
5055: - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
5057: Output Parameter:
5058: . mpimat - the parallel matrix generated
5060: Level: advanced
5062: Notes:
5063: The dimensions of the sequential matrix in each processor MUST be the same.
5064: The input seqmat is included into the container "Mat_Merge_SeqsToMPI", and will be
5065: destroyed when mpimat is destroyed. Call PetscObjectQuery() to access seqmat.
5066: @*/
5067: PetscErrorCode MatCreateMPIAIJSumSeqAIJ(MPI_Comm comm,Mat seqmat,PetscInt m,PetscInt n,MatReuse scall,Mat *mpimat)
5068: {
5070: PetscMPIInt size;
5073: MPI_Comm_size(comm,&size);
5074: if (size == 1) {
5075: PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);
5076: if (scall == MAT_INITIAL_MATRIX) {
5077: MatDuplicate(seqmat,MAT_COPY_VALUES,mpimat);
5078: } else {
5079: MatCopy(seqmat,*mpimat,SAME_NONZERO_PATTERN);
5080: }
5081: PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);
5082: return(0);
5083: }
5084: PetscLogEventBegin(MAT_Seqstompi,seqmat,0,0,0);
5085: if (scall == MAT_INITIAL_MATRIX) {
5086: MatCreateMPIAIJSumSeqAIJSymbolic(comm,seqmat,m,n,mpimat);
5087: }
5088: MatCreateMPIAIJSumSeqAIJNumeric(seqmat,*mpimat);
5089: PetscLogEventEnd(MAT_Seqstompi,seqmat,0,0,0);
5090: return(0);
5091: }
5093: /*@
5094: MatMPIAIJGetLocalMat - Creates a SeqAIJ from a MATMPIAIJ matrix by taking all its local rows and putting them into a sequential matrix with
5095: mlocal rows and n columns. Where mlocal is the row count obtained with MatGetLocalSize() and n is the global column count obtained
5096: with MatGetSize()
5098: Not Collective
5100: Input Parameters:
5101: + A - the matrix
5102: - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
5104: Output Parameter:
5105: . A_loc - the local sequential matrix generated
5107: Level: developer
5109: .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMatCondensed()
5111: @*/
5112: PetscErrorCode MatMPIAIJGetLocalMat(Mat A,MatReuse scall,Mat *A_loc)
5113: {
5115: Mat_MPIAIJ *mpimat=(Mat_MPIAIJ*)A->data;
5116: Mat_SeqAIJ *mat,*a,*b;
5117: PetscInt *ai,*aj,*bi,*bj,*cmap=mpimat->garray;
5118: MatScalar *aa,*ba,*cam;
5119: PetscScalar *ca;
5120: PetscInt am=A->rmap->n,i,j,k,cstart=A->cmap->rstart;
5121: PetscInt *ci,*cj,col,ncols_d,ncols_o,jo;
5122: PetscBool match;
5123: MPI_Comm comm;
5124: PetscMPIInt size;
5127: PetscStrbeginswith(((PetscObject)A)->type_name,MATMPIAIJ,&match);
5128: if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input");
5129: PetscObjectGetComm((PetscObject)A,&comm);
5130: MPI_Comm_size(comm,&size);
5131: if (size == 1 && scall == MAT_REUSE_MATRIX) return(0);
5133: PetscLogEventBegin(MAT_Getlocalmat,A,0,0,0);
5134: a = (Mat_SeqAIJ*)(mpimat->A)->data;
5135: b = (Mat_SeqAIJ*)(mpimat->B)->data;
5136: ai = a->i; aj = a->j; bi = b->i; bj = b->j;
5137: aa = a->a; ba = b->a;
5138: if (scall == MAT_INITIAL_MATRIX) {
5139: if (size == 1) {
5140: MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ai,aj,aa,A_loc);
5141: return(0);
5142: }
5144: PetscMalloc1(1+am,&ci);
5145: ci[0] = 0;
5146: for (i=0; i<am; i++) {
5147: ci[i+1] = ci[i] + (ai[i+1] - ai[i]) + (bi[i+1] - bi[i]);
5148: }
5149: PetscMalloc1(1+ci[am],&cj);
5150: PetscMalloc1(1+ci[am],&ca);
5151: k = 0;
5152: for (i=0; i<am; i++) {
5153: ncols_o = bi[i+1] - bi[i];
5154: ncols_d = ai[i+1] - ai[i];
5155: /* off-diagonal portion of A */
5156: for (jo=0; jo<ncols_o; jo++) {
5157: col = cmap[*bj];
5158: if (col >= cstart) break;
5159: cj[k] = col; bj++;
5160: ca[k++] = *ba++;
5161: }
5162: /* diagonal portion of A */
5163: for (j=0; j<ncols_d; j++) {
5164: cj[k] = cstart + *aj++;
5165: ca[k++] = *aa++;
5166: }
5167: /* off-diagonal portion of A */
5168: for (j=jo; j<ncols_o; j++) {
5169: cj[k] = cmap[*bj++];
5170: ca[k++] = *ba++;
5171: }
5172: }
5173: /* put together the new matrix */
5174: MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,am,A->cmap->N,ci,cj,ca,A_loc);
5175: /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
5176: /* Since these are PETSc arrays, change flags to free them as necessary. */
5177: mat = (Mat_SeqAIJ*)(*A_loc)->data;
5178: mat->free_a = PETSC_TRUE;
5179: mat->free_ij = PETSC_TRUE;
5180: mat->nonew = 0;
5181: } else if (scall == MAT_REUSE_MATRIX) {
5182: mat=(Mat_SeqAIJ*)(*A_loc)->data;
5183: ci = mat->i; cj = mat->j; cam = mat->a;
5184: for (i=0; i<am; i++) {
5185: /* off-diagonal portion of A */
5186: ncols_o = bi[i+1] - bi[i];
5187: for (jo=0; jo<ncols_o; jo++) {
5188: col = cmap[*bj];
5189: if (col >= cstart) break;
5190: *cam++ = *ba++; bj++;
5191: }
5192: /* diagonal portion of A */
5193: ncols_d = ai[i+1] - ai[i];
5194: for (j=0; j<ncols_d; j++) *cam++ = *aa++;
5195: /* off-diagonal portion of A */
5196: for (j=jo; j<ncols_o; j++) {
5197: *cam++ = *ba++; bj++;
5198: }
5199: }
5200: } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Invalid MatReuse %d",(int)scall);
5201: PetscLogEventEnd(MAT_Getlocalmat,A,0,0,0);
5202: return(0);
5203: }
5205: /*@C
5206: MatMPIAIJGetLocalMatCondensed - Creates a SeqAIJ matrix from an MATMPIAIJ matrix by taking all its local rows and NON-ZERO columns
5208: Not Collective
5210: Input Parameters:
5211: + A - the matrix
5212: . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
5213: - row, col - index sets of rows and columns to extract (or NULL)
5215: Output Parameter:
5216: . A_loc - the local sequential matrix generated
5218: Level: developer
5220: .seealso: MatGetOwnershipRange(), MatMPIAIJGetLocalMat()
5222: @*/
5223: PetscErrorCode MatMPIAIJGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc)
5224: {
5225: Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data;
5227: PetscInt i,start,end,ncols,nzA,nzB,*cmap,imark,*idx;
5228: IS isrowa,iscola;
5229: Mat *aloc;
5230: PetscBool match;
5233: PetscObjectTypeCompare((PetscObject)A,MATMPIAIJ,&match);
5234: if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPIAIJ matrix as input");
5235: PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);
5236: if (!row) {
5237: start = A->rmap->rstart; end = A->rmap->rend;
5238: ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);
5239: } else {
5240: isrowa = *row;
5241: }
5242: if (!col) {
5243: start = A->cmap->rstart;
5244: cmap = a->garray;
5245: nzA = a->A->cmap->n;
5246: nzB = a->B->cmap->n;
5247: PetscMalloc1(nzA+nzB, &idx);
5248: ncols = 0;
5249: for (i=0; i<nzB; i++) {
5250: if (cmap[i] < start) idx[ncols++] = cmap[i];
5251: else break;
5252: }
5253: imark = i;
5254: for (i=0; i<nzA; i++) idx[ncols++] = start + i;
5255: for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i];
5256: ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);
5257: } else {
5258: iscola = *col;
5259: }
5260: if (scall != MAT_INITIAL_MATRIX) {
5261: PetscMalloc1(1,&aloc);
5262: aloc[0] = *A_loc;
5263: }
5264: MatCreateSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);
5265: if (!col) { /* attach global id of condensed columns */
5266: PetscObjectCompose((PetscObject)aloc[0],"_petsc_GetLocalMatCondensed_iscol",(PetscObject)iscola);
5267: }
5268: *A_loc = aloc[0];
5269: PetscFree(aloc);
5270: if (!row) {
5271: ISDestroy(&isrowa);
5272: }
5273: if (!col) {
5274: ISDestroy(&iscola);
5275: }
5276: PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);
5277: return(0);
5278: }
5280: /*
5281: * Destroy a mat that may be composed with PetscSF communication objects.
5282: * The SF objects were created in MatCreateSeqSubMatrixWithRows_Private.
5283: * */
5284: PetscErrorCode MatDestroy_SeqAIJ_PetscSF(Mat mat)
5285: {
5286: PetscSF sf,osf;
5287: IS map;
5288: PetscErrorCode ierr;
5291: PetscObjectQuery((PetscObject)mat,"diagsf",(PetscObject*)&sf);
5292: PetscObjectQuery((PetscObject)mat,"offdiagsf",(PetscObject*)&osf);
5293: PetscSFDestroy(&sf);
5294: PetscSFDestroy(&osf);
5295: PetscObjectQuery((PetscObject)mat,"aoffdiagtopothmapping",(PetscObject*)&map);
5296: ISDestroy(&map);
5297: MatDestroy_SeqAIJ(mat);
5298: return(0);
5299: }
5301: /*
5302: * Create a sequential AIJ matrix based on row indices. a whole column is extracted once a row is matched.
5303: * Row could be local or remote.The routine is designed to be scalable in memory so that nothing is based
5304: * on a global size.
5305: * */
5306: PetscErrorCode MatCreateSeqSubMatrixWithRows_Private(Mat P,IS rows,Mat *P_oth)
5307: {
5308: Mat_MPIAIJ *p=(Mat_MPIAIJ*)P->data;
5309: Mat_SeqAIJ *pd=(Mat_SeqAIJ*)(p->A)->data,*po=(Mat_SeqAIJ*)(p->B)->data,*p_oth;
5310: PetscInt plocalsize,nrows,*ilocal,*oilocal,i,owner,lidx,*nrcols,*nlcols,ncol;
5311: PetscSFNode *iremote,*oiremote;
5312: const PetscInt *lrowindices;
5313: PetscErrorCode ierr;
5314: PetscSF sf,osf;
5315: PetscInt pcstart,*roffsets,*loffsets,*pnnz,j;
5316: PetscInt ontotalcols,dntotalcols,ntotalcols,nout;
5317: MPI_Comm comm;
5318: ISLocalToGlobalMapping mapping;
5321: PetscObjectGetComm((PetscObject)P,&comm);
5322: /* plocalsize is the number of roots
5323: * nrows is the number of leaves
5324: * */
5325: MatGetLocalSize(P,&plocalsize,NULL);
5326: ISGetLocalSize(rows,&nrows);
5327: PetscCalloc1(nrows,&iremote);
5328: ISGetIndices(rows,&lrowindices);
5329: for (i=0;i<nrows;i++) {
5330: /* Find a remote index and an owner for a row
5331: * The row could be local or remote
5332: * */
5333: owner = 0;
5334: lidx = 0;
5335: PetscLayoutFindOwnerIndex(P->rmap,lrowindices[i],&owner,&lidx);
5336: iremote[i].index = lidx;
5337: iremote[i].rank = owner;
5338: }
5339: /* Create SF to communicate how many nonzero columns for each row */
5340: PetscSFCreate(comm,&sf);
5341: /* SF will figure out the number of nonzero colunms for each row, and their
5342: * offsets
5343: * */
5344: PetscSFSetGraph(sf,plocalsize,nrows,NULL,PETSC_OWN_POINTER,iremote,PETSC_OWN_POINTER);
5345: PetscSFSetFromOptions(sf);
5346: PetscSFSetUp(sf);
5348: PetscCalloc1(2*(plocalsize+1),&roffsets);
5349: PetscCalloc1(2*plocalsize,&nrcols);
5350: PetscCalloc1(nrows,&pnnz);
5351: roffsets[0] = 0;
5352: roffsets[1] = 0;
5353: for (i=0;i<plocalsize;i++) {
5354: /* diag */
5355: nrcols[i*2+0] = pd->i[i+1] - pd->i[i];
5356: /* off diag */
5357: nrcols[i*2+1] = po->i[i+1] - po->i[i];
5358: /* compute offsets so that we relative location for each row */
5359: roffsets[(i+1)*2+0] = roffsets[i*2+0] + nrcols[i*2+0];
5360: roffsets[(i+1)*2+1] = roffsets[i*2+1] + nrcols[i*2+1];
5361: }
5362: PetscCalloc1(2*nrows,&nlcols);
5363: PetscCalloc1(2*nrows,&loffsets);
5364: /* 'r' means root, and 'l' means leaf */
5365: PetscSFBcastBegin(sf,MPIU_2INT,nrcols,nlcols);
5366: PetscSFBcastBegin(sf,MPIU_2INT,roffsets,loffsets);
5367: PetscSFBcastEnd(sf,MPIU_2INT,nrcols,nlcols);
5368: PetscSFBcastEnd(sf,MPIU_2INT,roffsets,loffsets);
5369: PetscSFDestroy(&sf);
5370: PetscFree(roffsets);
5371: PetscFree(nrcols);
5372: dntotalcols = 0;
5373: ontotalcols = 0;
5374: ncol = 0;
5375: for (i=0;i<nrows;i++) {
5376: pnnz[i] = nlcols[i*2+0] + nlcols[i*2+1];
5377: ncol = PetscMax(pnnz[i],ncol);
5378: /* diag */
5379: dntotalcols += nlcols[i*2+0];
5380: /* off diag */
5381: ontotalcols += nlcols[i*2+1];
5382: }
5383: /* We do not need to figure the right number of columns
5384: * since all the calculations will be done by going through the raw data
5385: * */
5386: MatCreateSeqAIJ(PETSC_COMM_SELF,nrows,ncol,0,pnnz,P_oth);
5387: MatSetUp(*P_oth);
5388: PetscFree(pnnz);
5389: p_oth = (Mat_SeqAIJ*) (*P_oth)->data;
5390: /* diag */
5391: PetscCalloc1(dntotalcols,&iremote);
5392: /* off diag */
5393: PetscCalloc1(ontotalcols,&oiremote);
5394: /* diag */
5395: PetscCalloc1(dntotalcols,&ilocal);
5396: /* off diag */
5397: PetscCalloc1(ontotalcols,&oilocal);
5398: dntotalcols = 0;
5399: ontotalcols = 0;
5400: ntotalcols = 0;
5401: for (i=0;i<nrows;i++) {
5402: owner = 0;
5403: PetscLayoutFindOwnerIndex(P->rmap,lrowindices[i],&owner,NULL);
5404: /* Set iremote for diag matrix */
5405: for (j=0;j<nlcols[i*2+0];j++) {
5406: iremote[dntotalcols].index = loffsets[i*2+0] + j;
5407: iremote[dntotalcols].rank = owner;
5408: /* P_oth is seqAIJ so that ilocal need to point to the first part of memory */
5409: ilocal[dntotalcols++] = ntotalcols++;
5410: }
5411: /* off diag */
5412: for (j=0;j<nlcols[i*2+1];j++) {
5413: oiremote[ontotalcols].index = loffsets[i*2+1] + j;
5414: oiremote[ontotalcols].rank = owner;
5415: oilocal[ontotalcols++] = ntotalcols++;
5416: }
5417: }
5418: ISRestoreIndices(rows,&lrowindices);
5419: PetscFree(loffsets);
5420: PetscFree(nlcols);
5421: PetscSFCreate(comm,&sf);
5422: /* P serves as roots and P_oth is leaves
5423: * Diag matrix
5424: * */
5425: PetscSFSetGraph(sf,pd->i[plocalsize],dntotalcols,ilocal,PETSC_OWN_POINTER,iremote,PETSC_OWN_POINTER);
5426: PetscSFSetFromOptions(sf);
5427: PetscSFSetUp(sf);
5429: PetscSFCreate(comm,&osf);
5430: /* Off diag */
5431: PetscSFSetGraph(osf,po->i[plocalsize],ontotalcols,oilocal,PETSC_OWN_POINTER,oiremote,PETSC_OWN_POINTER);
5432: PetscSFSetFromOptions(osf);
5433: PetscSFSetUp(osf);
5434: /* We operate on the matrix internal data for saving memory */
5435: PetscSFBcastBegin(sf,MPIU_SCALAR,pd->a,p_oth->a);
5436: PetscSFBcastBegin(osf,MPIU_SCALAR,po->a,p_oth->a);
5437: MatGetOwnershipRangeColumn(P,&pcstart,NULL);
5438: /* Convert to global indices for diag matrix */
5439: for (i=0;i<pd->i[plocalsize];i++) pd->j[i] += pcstart;
5440: PetscSFBcastBegin(sf,MPIU_INT,pd->j,p_oth->j);
5441: /* We want P_oth store global indices */
5442: ISLocalToGlobalMappingCreate(comm,1,p->B->cmap->n,p->garray,PETSC_COPY_VALUES,&mapping);
5443: /* Use memory scalable approach */
5444: ISLocalToGlobalMappingSetType(mapping,ISLOCALTOGLOBALMAPPINGHASH);
5445: ISLocalToGlobalMappingApply(mapping,po->i[plocalsize],po->j,po->j);
5446: PetscSFBcastBegin(osf,MPIU_INT,po->j,p_oth->j);
5447: PetscSFBcastEnd(sf,MPIU_INT,pd->j,p_oth->j);
5448: /* Convert back to local indices */
5449: for (i=0;i<pd->i[plocalsize];i++) pd->j[i] -= pcstart;
5450: PetscSFBcastEnd(osf,MPIU_INT,po->j,p_oth->j);
5451: nout = 0;
5452: ISGlobalToLocalMappingApply(mapping,IS_GTOLM_DROP,po->i[plocalsize],po->j,&nout,po->j);
5453: if (nout != po->i[plocalsize]) SETERRQ2(comm,PETSC_ERR_ARG_INCOMP,"n %D does not equal to nout %D \n",po->i[plocalsize],nout);
5454: ISLocalToGlobalMappingDestroy(&mapping);
5455: /* Exchange values */
5456: PetscSFBcastEnd(sf,MPIU_SCALAR,pd->a,p_oth->a);
5457: PetscSFBcastEnd(osf,MPIU_SCALAR,po->a,p_oth->a);
5458: /* Stop PETSc from shrinking memory */
5459: for (i=0;i<nrows;i++) p_oth->ilen[i] = p_oth->imax[i];
5460: MatAssemblyBegin(*P_oth,MAT_FINAL_ASSEMBLY);
5461: MatAssemblyEnd(*P_oth,MAT_FINAL_ASSEMBLY);
5462: /* Attach PetscSF objects to P_oth so that we can reuse it later */
5463: PetscObjectCompose((PetscObject)*P_oth,"diagsf",(PetscObject)sf);
5464: PetscObjectCompose((PetscObject)*P_oth,"offdiagsf",(PetscObject)osf);
5465: /* ``New MatDestroy" takes care of PetscSF objects as well */
5466: (*P_oth)->ops->destroy = MatDestroy_SeqAIJ_PetscSF;
5467: return(0);
5468: }
5470: /*
5471: * Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A
5472: * This supports MPIAIJ and MAIJ
5473: * */
5474: PetscErrorCode MatGetBrowsOfAcols_MPIXAIJ(Mat A,Mat P,PetscInt dof,MatReuse reuse,Mat *P_oth)
5475: {
5476: Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data,*p=(Mat_MPIAIJ*)P->data;
5477: Mat_SeqAIJ *p_oth;
5478: Mat_SeqAIJ *pd=(Mat_SeqAIJ*)(p->A)->data,*po=(Mat_SeqAIJ*)(p->B)->data;
5479: IS rows,map;
5480: PetscHMapI hamp;
5481: PetscInt i,htsize,*rowindices,off,*mapping,key,count;
5482: MPI_Comm comm;
5483: PetscSF sf,osf;
5484: PetscBool has;
5485: PetscErrorCode ierr;
5488: PetscObjectGetComm((PetscObject)A,&comm);
5489: PetscLogEventBegin(MAT_GetBrowsOfAocols,A,P,0,0);
5490: /* If it is the first time, create an index set of off-diag nonzero columns of A,
5491: * and then create a submatrix (that often is an overlapping matrix)
5492: * */
5493: if (reuse==MAT_INITIAL_MATRIX) {
5494: /* Use a hash table to figure out unique keys */
5495: PetscHMapICreate(&hamp);
5496: PetscHMapIResize(hamp,a->B->cmap->n);
5497: PetscCalloc1(a->B->cmap->n,&mapping);
5498: count = 0;
5499: /* Assume that a->g is sorted, otherwise the following does not make sense */
5500: for (i=0;i<a->B->cmap->n;i++) {
5501: key = a->garray[i]/dof;
5502: PetscHMapIHas(hamp,key,&has);
5503: if (!has) {
5504: mapping[i] = count;
5505: PetscHMapISet(hamp,key,count++);
5506: } else {
5507: /* Current 'i' has the same value the previous step */
5508: mapping[i] = count-1;
5509: }
5510: }
5511: ISCreateGeneral(comm,a->B->cmap->n,mapping,PETSC_OWN_POINTER,&map);
5512: PetscHMapIGetSize(hamp,&htsize);
5513: if (htsize!=count) SETERRQ2(comm,PETSC_ERR_ARG_INCOMP," Size of hash map %D is inconsistent with count %D \n",htsize,count);
5514: PetscCalloc1(htsize,&rowindices);
5515: off = 0;
5516: PetscHMapIGetKeys(hamp,&off,rowindices);
5517: PetscHMapIDestroy(&hamp);
5518: PetscSortInt(htsize,rowindices);
5519: ISCreateGeneral(comm,htsize,rowindices,PETSC_OWN_POINTER,&rows);
5520: /* In case, the matrix was already created but users want to recreate the matrix */
5521: MatDestroy(P_oth);
5522: MatCreateSeqSubMatrixWithRows_Private(P,rows,P_oth);
5523: PetscObjectCompose((PetscObject)*P_oth,"aoffdiagtopothmapping",(PetscObject)map);
5524: ISDestroy(&rows);
5525: } else if (reuse==MAT_REUSE_MATRIX) {
5526: /* If matrix was already created, we simply update values using SF objects
5527: * that as attached to the matrix ealier.
5528: * */
5529: PetscObjectQuery((PetscObject)*P_oth,"diagsf",(PetscObject*)&sf);
5530: PetscObjectQuery((PetscObject)*P_oth,"offdiagsf",(PetscObject*)&osf);
5531: if (!sf || !osf) {
5532: SETERRQ(comm,PETSC_ERR_ARG_NULL,"Matrix is not initialized yet \n");
5533: }
5534: p_oth = (Mat_SeqAIJ*) (*P_oth)->data;
5535: /* Update values in place */
5536: PetscSFBcastBegin(sf,MPIU_SCALAR,pd->a,p_oth->a);
5537: PetscSFBcastBegin(osf,MPIU_SCALAR,po->a,p_oth->a);
5538: PetscSFBcastEnd(sf,MPIU_SCALAR,pd->a,p_oth->a);
5539: PetscSFBcastEnd(osf,MPIU_SCALAR,po->a,p_oth->a);
5540: } else {
5541: SETERRQ(comm,PETSC_ERR_ARG_UNKNOWN_TYPE,"Unknown reuse type \n");
5542: }
5543: PetscLogEventEnd(MAT_GetBrowsOfAocols,A,P,0,0);
5544: return(0);
5545: }
5547: /*@C
5548: MatGetBrowsOfAcols - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns of local A
5550: Collective on Mat
5552: Input Parameters:
5553: + A,B - the matrices in mpiaij format
5554: . scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
5555: - rowb, colb - index sets of rows and columns of B to extract (or NULL)
5557: Output Parameter:
5558: + rowb, colb - index sets of rows and columns of B to extract
5559: - B_seq - the sequential matrix generated
5561: Level: developer
5563: @*/
5564: PetscErrorCode MatGetBrowsOfAcols(Mat A,Mat B,MatReuse scall,IS *rowb,IS *colb,Mat *B_seq)
5565: {
5566: Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data;
5568: PetscInt *idx,i,start,ncols,nzA,nzB,*cmap,imark;
5569: IS isrowb,iscolb;
5570: Mat *bseq=NULL;
5573: if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) {
5574: 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);
5575: }
5576: PetscLogEventBegin(MAT_GetBrowsOfAcols,A,B,0,0);
5578: if (scall == MAT_INITIAL_MATRIX) {
5579: start = A->cmap->rstart;
5580: cmap = a->garray;
5581: nzA = a->A->cmap->n;
5582: nzB = a->B->cmap->n;
5583: PetscMalloc1(nzA+nzB, &idx);
5584: ncols = 0;
5585: for (i=0; i<nzB; i++) { /* row < local row index */
5586: if (cmap[i] < start) idx[ncols++] = cmap[i];
5587: else break;
5588: }
5589: imark = i;
5590: for (i=0; i<nzA; i++) idx[ncols++] = start + i; /* local rows */
5591: for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i]; /* row > local row index */
5592: ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&isrowb);
5593: ISCreateStride(PETSC_COMM_SELF,B->cmap->N,0,1,&iscolb);
5594: } else {
5595: if (!rowb || !colb) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"IS rowb and colb must be provided for MAT_REUSE_MATRIX");
5596: isrowb = *rowb; iscolb = *colb;
5597: PetscMalloc1(1,&bseq);
5598: bseq[0] = *B_seq;
5599: }
5600: MatCreateSubMatrices(B,1,&isrowb,&iscolb,scall,&bseq);
5601: *B_seq = bseq[0];
5602: PetscFree(bseq);
5603: if (!rowb) {
5604: ISDestroy(&isrowb);
5605: } else {
5606: *rowb = isrowb;
5607: }
5608: if (!colb) {
5609: ISDestroy(&iscolb);
5610: } else {
5611: *colb = iscolb;
5612: }
5613: PetscLogEventEnd(MAT_GetBrowsOfAcols,A,B,0,0);
5614: return(0);
5615: }
5617: /*
5618: MatGetBrowsOfAoCols_MPIAIJ - Creates a SeqAIJ matrix by taking rows of B that equal to nonzero columns
5619: of the OFF-DIAGONAL portion of local A
5621: Collective on Mat
5623: Input Parameters:
5624: + A,B - the matrices in mpiaij format
5625: - scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
5627: Output Parameter:
5628: + startsj_s - starting point in B's sending j-arrays, saved for MAT_REUSE (or NULL)
5629: . startsj_r - starting point in B's receiving j-arrays, saved for MAT_REUSE (or NULL)
5630: . bufa_ptr - array for sending matrix values, saved for MAT_REUSE (or NULL)
5631: - B_oth - the sequential matrix generated with size aBn=a->B->cmap->n by B->cmap->N
5633: Developer Notes: This directly accesses information inside the VecScatter associated with the matrix-vector product
5634: for this matrix. This is not desirable..
5636: Level: developer
5638: */
5639: PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscInt **startsj_s,PetscInt **startsj_r,MatScalar **bufa_ptr,Mat *B_oth)
5640: {
5641: PetscErrorCode ierr;
5642: Mat_MPIAIJ *a=(Mat_MPIAIJ*)A->data;
5643: Mat_SeqAIJ *b_oth;
5644: VecScatter ctx;
5645: MPI_Comm comm;
5646: const PetscMPIInt *rprocs,*sprocs;
5647: const PetscInt *srow,*rstarts,*sstarts;
5648: PetscInt *rowlen,*bufj,*bufJ,ncols,aBn=a->B->cmap->n,row,*b_othi,*b_othj,*rvalues=NULL,*svalues=NULL,*cols,sbs,rbs;
5649: PetscInt i,j,k=0,l,ll,nrecvs,nsends,nrows,*rstartsj = 0,*sstartsj,len;
5650: PetscScalar *b_otha,*bufa,*bufA,*vals;
5651: MPI_Request *rwaits = NULL,*swaits = NULL;
5652: MPI_Status rstatus;
5653: PetscMPIInt jj,size,tag,rank,nsends_mpi,nrecvs_mpi;
5656: PetscObjectGetComm((PetscObject)A,&comm);
5657: MPI_Comm_size(comm,&size);
5659: if (A->cmap->rstart != B->rmap->rstart || A->cmap->rend != B->rmap->rend) {
5660: 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);
5661: }
5662: PetscLogEventBegin(MAT_GetBrowsOfAocols,A,B,0,0);
5663: MPI_Comm_rank(comm,&rank);
5665: if (size == 1) {
5666: startsj_s = NULL;
5667: bufa_ptr = NULL;
5668: *B_oth = NULL;
5669: return(0);
5670: }
5672: ctx = a->Mvctx;
5673: tag = ((PetscObject)ctx)->tag;
5675: if (ctx->inuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE," Scatter ctx already in use");
5676: VecScatterGetRemote_Private(ctx,PETSC_TRUE/*send*/,&nsends,&sstarts,&srow,&sprocs,&sbs);
5677: /* rprocs[] must be ordered so that indices received from them are ordered in rvalues[], which is key to algorithms used in this subroutine */
5678: VecScatterGetRemoteOrdered_Private(ctx,PETSC_FALSE/*recv*/,&nrecvs,&rstarts,NULL/*indices not needed*/,&rprocs,&rbs);
5679: PetscMPIIntCast(nsends,&nsends_mpi);
5680: PetscMPIIntCast(nrecvs,&nrecvs_mpi);
5681: PetscMalloc2(nrecvs,&rwaits,nsends,&swaits);
5683: if (!startsj_s || !bufa_ptr) scall = MAT_INITIAL_MATRIX;
5684: if (scall == MAT_INITIAL_MATRIX) {
5685: /* i-array */
5686: /*---------*/
5687: /* post receives */
5688: if (nrecvs) {PetscMalloc1(rbs*(rstarts[nrecvs] - rstarts[0]),&rvalues);} /* rstarts can be NULL when nrecvs=0 */
5689: for (i=0; i<nrecvs; i++) {
5690: rowlen = rvalues + rstarts[i]*rbs;
5691: nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of indices to be received */
5692: MPI_Irecv(rowlen,nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);
5693: }
5695: /* pack the outgoing message */
5696: PetscMalloc2(nsends+1,&sstartsj,nrecvs+1,&rstartsj);
5698: sstartsj[0] = 0;
5699: rstartsj[0] = 0;
5700: len = 0; /* total length of j or a array to be sent */
5701: if (nsends) {
5702: k = sstarts[0]; /* ATTENTION: sstarts[0] and rstarts[0] are not necessarily zero */
5703: PetscMalloc1(sbs*(sstarts[nsends]-sstarts[0]),&svalues);
5704: }
5705: for (i=0; i<nsends; i++) {
5706: rowlen = svalues + (sstarts[i]-sstarts[0])*sbs;
5707: nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
5708: for (j=0; j<nrows; j++) {
5709: row = srow[k] + B->rmap->range[rank]; /* global row idx */
5710: for (l=0; l<sbs; l++) {
5711: MatGetRow_MPIAIJ(B,row+l,&ncols,NULL,NULL); /* rowlength */
5713: rowlen[j*sbs+l] = ncols;
5715: len += ncols;
5716: MatRestoreRow_MPIAIJ(B,row+l,&ncols,NULL,NULL);
5717: }
5718: k++;
5719: }
5720: MPI_Isend(rowlen,nrows*sbs,MPIU_INT,sprocs[i],tag,comm,swaits+i);
5722: sstartsj[i+1] = len; /* starting point of (i+1)-th outgoing msg in bufj and bufa */
5723: }
5724: /* recvs and sends of i-array are completed */
5725: i = nrecvs;
5726: while (i--) {
5727: MPI_Waitany(nrecvs_mpi,rwaits,&jj,&rstatus);
5728: }
5729: if (nsends) {MPI_Waitall(nsends_mpi,swaits,MPI_STATUSES_IGNORE);}
5730: PetscFree(svalues);
5732: /* allocate buffers for sending j and a arrays */
5733: PetscMalloc1(len+1,&bufj);
5734: PetscMalloc1(len+1,&bufa);
5736: /* create i-array of B_oth */
5737: PetscMalloc1(aBn+2,&b_othi);
5739: b_othi[0] = 0;
5740: len = 0; /* total length of j or a array to be received */
5741: k = 0;
5742: for (i=0; i<nrecvs; i++) {
5743: rowlen = rvalues + (rstarts[i]-rstarts[0])*rbs;
5744: nrows = (rstarts[i+1]-rstarts[i])*rbs; /* num of rows to be received */
5745: for (j=0; j<nrows; j++) {
5746: b_othi[k+1] = b_othi[k] + rowlen[j];
5747: PetscIntSumError(rowlen[j],len,&len);
5748: k++;
5749: }
5750: rstartsj[i+1] = len; /* starting point of (i+1)-th incoming msg in bufj and bufa */
5751: }
5752: PetscFree(rvalues);
5754: /* allocate space for j and a arrrays of B_oth */
5755: PetscMalloc1(b_othi[aBn]+1,&b_othj);
5756: PetscMalloc1(b_othi[aBn]+1,&b_otha);
5758: /* j-array */
5759: /*---------*/
5760: /* post receives of j-array */
5761: for (i=0; i<nrecvs; i++) {
5762: nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */
5763: MPI_Irecv(b_othj+rstartsj[i],nrows,MPIU_INT,rprocs[i],tag,comm,rwaits+i);
5764: }
5766: /* pack the outgoing message j-array */
5767: if (nsends) k = sstarts[0];
5768: for (i=0; i<nsends; i++) {
5769: nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
5770: bufJ = bufj+sstartsj[i];
5771: for (j=0; j<nrows; j++) {
5772: row = srow[k++] + B->rmap->range[rank]; /* global row idx */
5773: for (ll=0; ll<sbs; ll++) {
5774: MatGetRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);
5775: for (l=0; l<ncols; l++) {
5776: *bufJ++ = cols[l];
5777: }
5778: MatRestoreRow_MPIAIJ(B,row+ll,&ncols,&cols,NULL);
5779: }
5780: }
5781: MPI_Isend(bufj+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_INT,sprocs[i],tag,comm,swaits+i);
5782: }
5784: /* recvs and sends of j-array are completed */
5785: i = nrecvs;
5786: while (i--) {
5787: MPI_Waitany(nrecvs_mpi,rwaits,&jj,&rstatus);
5788: }
5789: if (nsends) {MPI_Waitall(nsends_mpi,swaits,MPI_STATUSES_IGNORE);}
5790: } else if (scall == MAT_REUSE_MATRIX) {
5791: sstartsj = *startsj_s;
5792: rstartsj = *startsj_r;
5793: bufa = *bufa_ptr;
5794: b_oth = (Mat_SeqAIJ*)(*B_oth)->data;
5795: b_otha = b_oth->a;
5796: } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE, "Matrix P does not posses an object container");
5798: /* a-array */
5799: /*---------*/
5800: /* post receives of a-array */
5801: for (i=0; i<nrecvs; i++) {
5802: nrows = rstartsj[i+1]-rstartsj[i]; /* length of the msg received */
5803: MPI_Irecv(b_otha+rstartsj[i],nrows,MPIU_SCALAR,rprocs[i],tag,comm,rwaits+i);
5804: }
5806: /* pack the outgoing message a-array */
5807: if (nsends) k = sstarts[0];
5808: for (i=0; i<nsends; i++) {
5809: nrows = sstarts[i+1]-sstarts[i]; /* num of block rows */
5810: bufA = bufa+sstartsj[i];
5811: for (j=0; j<nrows; j++) {
5812: row = srow[k++] + B->rmap->range[rank]; /* global row idx */
5813: for (ll=0; ll<sbs; ll++) {
5814: MatGetRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);
5815: for (l=0; l<ncols; l++) {
5816: *bufA++ = vals[l];
5817: }
5818: MatRestoreRow_MPIAIJ(B,row+ll,&ncols,NULL,&vals);
5819: }
5820: }
5821: MPI_Isend(bufa+sstartsj[i],sstartsj[i+1]-sstartsj[i],MPIU_SCALAR,sprocs[i],tag,comm,swaits+i);
5822: }
5823: /* recvs and sends of a-array are completed */
5824: i = nrecvs;
5825: while (i--) {
5826: MPI_Waitany(nrecvs_mpi,rwaits,&jj,&rstatus);
5827: }
5828: if (nsends) {MPI_Waitall(nsends_mpi,swaits,MPI_STATUSES_IGNORE);}
5829: PetscFree2(rwaits,swaits);
5831: if (scall == MAT_INITIAL_MATRIX) {
5832: /* put together the new matrix */
5833: MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,aBn,B->cmap->N,b_othi,b_othj,b_otha,B_oth);
5835: /* MatCreateSeqAIJWithArrays flags matrix so PETSc doesn't free the user's arrays. */
5836: /* Since these are PETSc arrays, change flags to free them as necessary. */
5837: b_oth = (Mat_SeqAIJ*)(*B_oth)->data;
5838: b_oth->free_a = PETSC_TRUE;
5839: b_oth->free_ij = PETSC_TRUE;
5840: b_oth->nonew = 0;
5842: PetscFree(bufj);
5843: if (!startsj_s || !bufa_ptr) {
5844: PetscFree2(sstartsj,rstartsj);
5845: PetscFree(bufa_ptr);
5846: } else {
5847: *startsj_s = sstartsj;
5848: *startsj_r = rstartsj;
5849: *bufa_ptr = bufa;
5850: }
5851: }
5853: VecScatterRestoreRemote_Private(ctx,PETSC_TRUE,&nsends,&sstarts,&srow,&sprocs,&sbs);
5854: VecScatterRestoreRemoteOrdered_Private(ctx,PETSC_FALSE,&nrecvs,&rstarts,NULL,&rprocs,&rbs);
5855: PetscLogEventEnd(MAT_GetBrowsOfAocols,A,B,0,0);
5856: return(0);
5857: }
5859: /*@C
5860: MatGetCommunicationStructs - Provides access to the communication structures used in matrix-vector multiplication.
5862: Not Collective
5864: Input Parameters:
5865: . A - The matrix in mpiaij format
5867: Output Parameter:
5868: + lvec - The local vector holding off-process values from the argument to a matrix-vector product
5869: . colmap - A map from global column index to local index into lvec
5870: - multScatter - A scatter from the argument of a matrix-vector product to lvec
5872: Level: developer
5874: @*/
5875: #if defined(PETSC_USE_CTABLE)
5876: PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscTable *colmap, VecScatter *multScatter)
5877: #else
5878: PetscErrorCode MatGetCommunicationStructs(Mat A, Vec *lvec, PetscInt *colmap[], VecScatter *multScatter)
5879: #endif
5880: {
5881: Mat_MPIAIJ *a;
5888: a = (Mat_MPIAIJ*) A->data;
5889: if (lvec) *lvec = a->lvec;
5890: if (colmap) *colmap = a->colmap;
5891: if (multScatter) *multScatter = a->Mvctx;
5892: return(0);
5893: }
5895: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJCRL(Mat,MatType,MatReuse,Mat*);
5896: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat,MatType,MatReuse,Mat*);
5897: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJSELL(Mat,MatType,MatReuse,Mat*);
5898: #if defined(PETSC_HAVE_MKL_SPARSE)
5899: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJMKL(Mat,MatType,MatReuse,Mat*);
5900: #endif
5901: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPISBAIJ(Mat,MatType,MatReuse,Mat*);
5902: #if defined(PETSC_HAVE_ELEMENTAL)
5903: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_Elemental(Mat,MatType,MatReuse,Mat*);
5904: #endif
5905: #if defined(PETSC_HAVE_HYPRE)
5906: PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat,MatType,MatReuse,Mat*);
5907: PETSC_INTERN PetscErrorCode MatMatMatMult_Transpose_AIJ_AIJ(Mat,Mat,Mat,MatReuse,PetscReal,Mat*);
5908: #endif
5909: PETSC_INTERN PetscErrorCode MatConvert_XAIJ_IS(Mat,MatType,MatReuse,Mat*);
5910: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPISELL(Mat,MatType,MatReuse,Mat*);
5911: PETSC_INTERN PetscErrorCode MatPtAP_IS_XAIJ(Mat,Mat,MatReuse,PetscReal,Mat*);
5913: /*
5914: Computes (B'*A')' since computing B*A directly is untenable
5916: n p p
5917: ( ) ( ) ( )
5918: m ( A ) * n ( B ) = m ( C )
5919: ( ) ( ) ( )
5921: */
5922: PetscErrorCode MatMatMultNumeric_MPIDense_MPIAIJ(Mat A,Mat B,Mat C)
5923: {
5925: Mat At,Bt,Ct;
5928: MatTranspose(A,MAT_INITIAL_MATRIX,&At);
5929: MatTranspose(B,MAT_INITIAL_MATRIX,&Bt);
5930: MatMatMult(Bt,At,MAT_INITIAL_MATRIX,1.0,&Ct);
5931: MatDestroy(&At);
5932: MatDestroy(&Bt);
5933: MatTranspose(Ct,MAT_REUSE_MATRIX,&C);
5934: MatDestroy(&Ct);
5935: return(0);
5936: }
5938: PetscErrorCode MatMatMultSymbolic_MPIDense_MPIAIJ(Mat A,Mat B,PetscReal fill,Mat *C)
5939: {
5941: PetscInt m=A->rmap->n,n=B->cmap->n;
5942: Mat Cmat;
5945: 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);
5946: MatCreate(PetscObjectComm((PetscObject)A),&Cmat);
5947: MatSetSizes(Cmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
5948: MatSetBlockSizesFromMats(Cmat,A,B);
5949: MatSetType(Cmat,MATMPIDENSE);
5950: MatMPIDenseSetPreallocation(Cmat,NULL);
5951: MatAssemblyBegin(Cmat,MAT_FINAL_ASSEMBLY);
5952: MatAssemblyEnd(Cmat,MAT_FINAL_ASSEMBLY);
5954: Cmat->ops->matmultnumeric = MatMatMultNumeric_MPIDense_MPIAIJ;
5956: *C = Cmat;
5957: return(0);
5958: }
5960: /* ----------------------------------------------------------------*/
5961: PETSC_INTERN PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C)
5962: {
5966: if (scall == MAT_INITIAL_MATRIX) {
5967: PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);
5968: MatMatMultSymbolic_MPIDense_MPIAIJ(A,B,fill,C);
5969: PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);
5970: }
5971: PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);
5972: MatMatMultNumeric_MPIDense_MPIAIJ(A,B,*C);
5973: PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);
5974: return(0);
5975: }
5977: /*MC
5978: MATMPIAIJ - MATMPIAIJ = "mpiaij" - A matrix type to be used for parallel sparse matrices.
5980: Options Database Keys:
5981: . -mat_type mpiaij - sets the matrix type to "mpiaij" during a call to MatSetFromOptions()
5983: Level: beginner
5985: Notes:
5986: MatSetValues() may be called for this matrix type with a NULL argument for the numerical values,
5987: in this case the values associated with the rows and columns one passes in are set to zero
5988: in the matrix
5990: MatSetOptions(,MAT_STRUCTURE_ONLY,PETSC_TRUE) may be called for this matrix type. In this no
5991: space is allocated for the nonzero entries and any entries passed with MatSetValues() are ignored
5993: .seealso: MatCreateAIJ()
5994: M*/
5996: PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat B)
5997: {
5998: Mat_MPIAIJ *b;
6000: PetscMPIInt size;
6003: MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);
6005: PetscNewLog(B,&b);
6006: B->data = (void*)b;
6007: PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
6008: B->assembled = PETSC_FALSE;
6009: B->insertmode = NOT_SET_VALUES;
6010: b->size = size;
6012: MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);
6014: /* build cache for off array entries formed */
6015: MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);
6017: b->donotstash = PETSC_FALSE;
6018: b->colmap = 0;
6019: b->garray = 0;
6020: b->roworiented = PETSC_TRUE;
6022: /* stuff used for matrix vector multiply */
6023: b->lvec = NULL;
6024: b->Mvctx = NULL;
6026: /* stuff for MatGetRow() */
6027: b->rowindices = 0;
6028: b->rowvalues = 0;
6029: b->getrowactive = PETSC_FALSE;
6031: /* flexible pointer used in CUSP/CUSPARSE classes */
6032: b->spptr = NULL;
6034: PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetUseScalableIncreaseOverlap_C",MatMPIAIJSetUseScalableIncreaseOverlap_MPIAIJ);
6035: PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIAIJ);
6036: PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIAIJ);
6037: PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPIAIJ);
6038: PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJ);
6039: PetscObjectComposeFunction((PetscObject)B,"MatResetPreallocation_C",MatResetPreallocation_MPIAIJ);
6040: PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocationCSR_C",MatMPIAIJSetPreallocationCSR_MPIAIJ);
6041: PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIAIJ);
6042: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijperm_C",MatConvert_MPIAIJ_MPIAIJPERM);
6043: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijsell_C",MatConvert_MPIAIJ_MPIAIJSELL);
6044: #if defined(PETSC_HAVE_MKL_SPARSE)
6045: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijmkl_C",MatConvert_MPIAIJ_MPIAIJMKL);
6046: #endif
6047: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpiaijcrl_C",MatConvert_MPIAIJ_MPIAIJCRL);
6048: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisbaij_C",MatConvert_MPIAIJ_MPISBAIJ);
6049: #if defined(PETSC_HAVE_ELEMENTAL)
6050: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_elemental_C",MatConvert_MPIAIJ_Elemental);
6051: #endif
6052: #if defined(PETSC_HAVE_HYPRE)
6053: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_hypre_C",MatConvert_AIJ_HYPRE);
6054: #endif
6055: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_is_C",MatConvert_XAIJ_IS);
6056: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpiaij_mpisell_C",MatConvert_MPIAIJ_MPISELL);
6057: PetscObjectComposeFunction((PetscObject)B,"MatMatMult_mpidense_mpiaij_C",MatMatMult_MPIDense_MPIAIJ);
6058: PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_mpidense_mpiaij_C",MatMatMultSymbolic_MPIDense_MPIAIJ);
6059: PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_mpidense_mpiaij_C",MatMatMultNumeric_MPIDense_MPIAIJ);
6060: #if defined(PETSC_HAVE_HYPRE)
6061: PetscObjectComposeFunction((PetscObject)B,"MatMatMatMult_transpose_mpiaij_mpiaij_C",MatMatMatMult_Transpose_AIJ_AIJ);
6062: #endif
6063: PetscObjectComposeFunction((PetscObject)B,"MatPtAP_is_mpiaij_C",MatPtAP_IS_XAIJ);
6064: PetscObjectChangeTypeName((PetscObject)B,MATMPIAIJ);
6065: return(0);
6066: }
6068: /*@C
6069: MatCreateMPIAIJWithSplitArrays - creates a MPI AIJ matrix using arrays that contain the "diagonal"
6070: and "off-diagonal" part of the matrix in CSR format.
6072: Collective
6074: Input Parameters:
6075: + comm - MPI communicator
6076: . m - number of local rows (Cannot be PETSC_DECIDE)
6077: . n - This value should be the same as the local size used in creating the
6078: x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
6079: calculated if N is given) For square matrices n is almost always m.
6080: . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
6081: . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
6082: . i - row indices for "diagonal" portion of matrix; that is i[0] = 0, i[row] = i[row-1] + number of elements in that row of the matrix
6083: . j - column indices
6084: . a - matrix values
6085: . oi - row indices for "off-diagonal" portion of matrix; that is oi[0] = 0, oi[row] = oi[row-1] + number of elements in that row of the matrix
6086: . oj - column indices
6087: - oa - matrix values
6089: Output Parameter:
6090: . mat - the matrix
6092: Level: advanced
6094: Notes:
6095: The i, j, and a arrays ARE NOT copied by this routine into the internal format used by PETSc. The user
6096: must free the arrays once the matrix has been destroyed and not before.
6098: The i and j indices are 0 based
6100: See MatCreateAIJ() for the definition of "diagonal" and "off-diagonal" portion of the matrix
6102: This sets local rows and cannot be used to set off-processor values.
6104: Use of this routine is discouraged because it is inflexible and cumbersome to use. It is extremely rare that a
6105: legacy application natively assembles into exactly this split format. The code to do so is nontrivial and does
6106: not easily support in-place reassembly. It is recommended to use MatSetValues() (or a variant thereof) because
6107: the resulting assembly is easier to implement, will work with any matrix format, and the user does not have to
6108: keep track of the underlying array. Use MatSetOption(A,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) to disable all
6109: communication if it is known that only local entries will be set.
6111: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
6112: MATMPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithArrays()
6113: @*/
6114: 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)
6115: {
6117: Mat_MPIAIJ *maij;
6120: if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
6121: if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
6122: if (oi[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"oi (row indices) must start with 0");
6123: MatCreate(comm,mat);
6124: MatSetSizes(*mat,m,n,M,N);
6125: MatSetType(*mat,MATMPIAIJ);
6126: maij = (Mat_MPIAIJ*) (*mat)->data;
6128: (*mat)->preallocated = PETSC_TRUE;
6130: PetscLayoutSetUp((*mat)->rmap);
6131: PetscLayoutSetUp((*mat)->cmap);
6133: MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,n,i,j,a,&maij->A);
6134: MatCreateSeqAIJWithArrays(PETSC_COMM_SELF,m,(*mat)->cmap->N,oi,oj,oa,&maij->B);
6136: MatAssemblyBegin(maij->A,MAT_FINAL_ASSEMBLY);
6137: MatAssemblyEnd(maij->A,MAT_FINAL_ASSEMBLY);
6138: MatAssemblyBegin(maij->B,MAT_FINAL_ASSEMBLY);
6139: MatAssemblyEnd(maij->B,MAT_FINAL_ASSEMBLY);
6141: MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE);
6142: MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);
6143: MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);
6144: MatSetOption(*mat,MAT_NO_OFF_PROC_ENTRIES,PETSC_FALSE);
6145: MatSetOption(*mat,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
6146: return(0);
6147: }
6149: /*
6150: Special version for direct calls from Fortran
6151: */
6152: #include <petsc/private/fortranimpl.h>
6154: /* Change these macros so can be used in void function */
6155: #undef CHKERRQ
6156: #define CHKERRQ(ierr) CHKERRABORT(PETSC_COMM_WORLD,ierr)
6157: #undef SETERRQ2
6158: #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr)
6159: #undef SETERRQ3
6160: #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr)
6161: #undef SETERRQ
6162: #define SETERRQ(c,ierr,b) CHKERRABORT(c,ierr)
6164: #if defined(PETSC_HAVE_FORTRAN_CAPS)
6165: #define matsetvaluesmpiaij_ MATSETVALUESMPIAIJ
6166: #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
6167: #define matsetvaluesmpiaij_ matsetvaluesmpiaij
6168: #else
6169: #endif
6170: 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)
6171: {
6172: Mat mat = *mmat;
6173: PetscInt m = *mm, n = *mn;
6174: InsertMode addv = *maddv;
6175: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
6176: PetscScalar value;
6179: MatCheckPreallocated(mat,1);
6180: if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv;
6182: #if defined(PETSC_USE_DEBUG)
6183: else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values");
6184: #endif
6185: {
6186: PetscInt i,j,rstart = mat->rmap->rstart,rend = mat->rmap->rend;
6187: PetscInt cstart = mat->cmap->rstart,cend = mat->cmap->rend,row,col;
6188: PetscBool roworiented = aij->roworiented;
6190: /* Some Variables required in the macro */
6191: Mat A = aij->A;
6192: Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data;
6193: PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j;
6194: MatScalar *aa = a->a;
6195: PetscBool ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES)) ? PETSC_TRUE : PETSC_FALSE);
6196: Mat B = aij->B;
6197: Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data;
6198: PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap->n,am = aij->A->rmap->n;
6199: MatScalar *ba = b->a;
6201: PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2;
6202: PetscInt nonew = a->nonew;
6203: MatScalar *ap1,*ap2;
6206: for (i=0; i<m; i++) {
6207: if (im[i] < 0) continue;
6208: #if defined(PETSC_USE_DEBUG)
6209: 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);
6210: #endif
6211: if (im[i] >= rstart && im[i] < rend) {
6212: row = im[i] - rstart;
6213: lastcol1 = -1;
6214: rp1 = aj + ai[row];
6215: ap1 = aa + ai[row];
6216: rmax1 = aimax[row];
6217: nrow1 = ailen[row];
6218: low1 = 0;
6219: high1 = nrow1;
6220: lastcol2 = -1;
6221: rp2 = bj + bi[row];
6222: ap2 = ba + bi[row];
6223: rmax2 = bimax[row];
6224: nrow2 = bilen[row];
6225: low2 = 0;
6226: high2 = nrow2;
6228: for (j=0; j<n; j++) {
6229: if (roworiented) value = v[i*n+j];
6230: else value = v[i+j*m];
6231: if (in[j] >= cstart && in[j] < cend) {
6232: col = in[j] - cstart;
6233: if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue;
6234: MatSetValues_SeqAIJ_A_Private(row,col,value,addv,im[i],in[j]);
6235: } else if (in[j] < 0) continue;
6236: #if defined(PETSC_USE_DEBUG)
6237: /* extra brace on SETERRQ2() is required for --with-errorchecking=0 - due to the next 'else' clause */
6238: 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);}
6239: #endif
6240: else {
6241: if (mat->was_assembled) {
6242: if (!aij->colmap) {
6243: MatCreateColmap_MPIAIJ_Private(mat);
6244: }
6245: #if defined(PETSC_USE_CTABLE)
6246: PetscTableFind(aij->colmap,in[j]+1,&col);
6247: col--;
6248: #else
6249: col = aij->colmap[in[j]] - 1;
6250: #endif
6251: if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES) && row != col) continue;
6252: if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) {
6253: MatDisAssemble_MPIAIJ(mat);
6254: col = in[j];
6255: /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */
6256: B = aij->B;
6257: b = (Mat_SeqAIJ*)B->data;
6258: bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j;
6259: rp2 = bj + bi[row];
6260: ap2 = ba + bi[row];
6261: rmax2 = bimax[row];
6262: nrow2 = bilen[row];
6263: low2 = 0;
6264: high2 = nrow2;
6265: bm = aij->B->rmap->n;
6266: ba = b->a;
6267: }
6268: } else col = in[j];
6269: MatSetValues_SeqAIJ_B_Private(row,col,value,addv,im[i],in[j]);
6270: }
6271: }
6272: } else if (!aij->donotstash) {
6273: if (roworiented) {
6274: MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
6275: } else {
6276: MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
6277: }
6278: }
6279: }
6280: }
6281: PetscFunctionReturnVoid();
6282: }