Actual source code: mpiaij.c
1: #define PETSCMAT_DLL
3: #include src/mat/impls/aij/mpi/mpiaij.h
4: #include src/inline/spops.h
6: /*
7: Local utility routine that creates a mapping from the global column
8: number to the local number in the off-diagonal part of the local
9: storage of the matrix. When PETSC_USE_CTABLE is used this is scalable at
10: a slightly higher hash table cost; without it it is not scalable (each processor
11: has an order N integer array but is fast to acess.
12: */
15: PetscErrorCode CreateColmap_MPIAIJ_Private(Mat mat)
16: {
17: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
19: PetscInt n = aij->B->cmap.n,i;
22: #if defined (PETSC_USE_CTABLE)
23: PetscTableCreate(n,&aij->colmap);
24: for (i=0; i<n; i++){
25: PetscTableAdd(aij->colmap,aij->garray[i]+1,i+1);
26: }
27: #else
28: PetscMalloc((mat->cmap.N+1)*sizeof(PetscInt),&aij->colmap);
29: PetscLogObjectMemory(mat,mat->cmap.N*sizeof(PetscInt));
30: PetscMemzero(aij->colmap,mat->cmap.N*sizeof(PetscInt));
31: for (i=0; i<n; i++) aij->colmap[aij->garray[i]] = i+1;
32: #endif
33: return(0);
34: }
37: #define CHUNKSIZE 15
38: #define MatSetValues_SeqAIJ_A_Private(row,col,value,addv) \
39: { \
40: if (col <= lastcol1) low1 = 0; else high1 = nrow1; \
41: lastcol1 = col;\
42: while (high1-low1 > 5) { \
43: t = (low1+high1)/2; \
44: if (rp1[t] > col) high1 = t; \
45: else low1 = t; \
46: } \
47: for (_i=low1; _i<high1; _i++) { \
48: if (rp1[_i] > col) break; \
49: if (rp1[_i] == col) { \
50: if (addv == ADD_VALUES) ap1[_i] += value; \
51: else ap1[_i] = value; \
52: goto a_noinsert; \
53: } \
54: } \
55: if (value == 0.0 && ignorezeroentries) goto a_noinsert; \
56: if (nonew == 1) goto a_noinsert; \
57: if (nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \
58: MatSeqXAIJReallocateAIJ(A,am,1,nrow1,row,col,rmax1,aa,ai,aj,rp1,ap1,aimax,nonew,MatScalar); \
59: N = nrow1++ - 1; a->nz++; high1++; \
60: /* shift up all the later entries in this row */ \
61: for (ii=N; ii>=_i; ii--) { \
62: rp1[ii+1] = rp1[ii]; \
63: ap1[ii+1] = ap1[ii]; \
64: } \
65: rp1[_i] = col; \
66: ap1[_i] = value; \
67: a_noinsert: ; \
68: ailen[row] = nrow1; \
69: }
72: #define MatSetValues_SeqAIJ_B_Private(row,col,value,addv) \
73: { \
74: if (col <= lastcol2) low2 = 0; else high2 = nrow2; \
75: lastcol2 = col;\
76: while (high2-low2 > 5) { \
77: t = (low2+high2)/2; \
78: if (rp2[t] > col) high2 = t; \
79: else low2 = t; \
80: } \
81: for (_i=low2; _i<high2; _i++) { \
82: if (rp2[_i] > col) break; \
83: if (rp2[_i] == col) { \
84: if (addv == ADD_VALUES) ap2[_i] += value; \
85: else ap2[_i] = value; \
86: goto b_noinsert; \
87: } \
88: } \
89: if (value == 0.0 && ignorezeroentries) goto b_noinsert; \
90: if (nonew == 1) goto b_noinsert; \
91: if (nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \
92: MatSeqXAIJReallocateAIJ(B,bm,1,nrow2,row,col,rmax2,ba,bi,bj,rp2,ap2,bimax,nonew,MatScalar); \
93: N = nrow2++ - 1; b->nz++; high2++;\
94: /* shift up all the later entries in this row */ \
95: for (ii=N; ii>=_i; ii--) { \
96: rp2[ii+1] = rp2[ii]; \
97: ap2[ii+1] = ap2[ii]; \
98: } \
99: rp2[_i] = col; \
100: ap2[_i] = value; \
101: b_noinsert: ; \
102: bilen[row] = nrow2; \
103: }
107: PetscErrorCode MatSetValuesRow_MPIAIJ(Mat A,PetscInt row,const PetscScalar v[])
108: {
109: Mat_MPIAIJ *mat = (Mat_MPIAIJ*)A->data;
110: Mat_SeqAIJ *a = (Mat_SeqAIJ*)mat->A->data,*b = (Mat_SeqAIJ*)mat->B->data;
112: PetscInt l,*garray = mat->garray,diag;
115: /* code only works for square matrices A */
117: /* find size of row to the left of the diagonal part */
118: MatGetOwnershipRange(A,&diag,0);
119: row = row - diag;
120: for (l=0; l<b->i[row+1]-b->i[row]; l++) {
121: if (garray[b->j[b->i[row]+l]] > diag) break;
122: }
123: PetscMemcpy(b->a+b->i[row],v,l*sizeof(PetscScalar));
125: /* diagonal part */
126: PetscMemcpy(a->a+a->i[row],v+l,(a->i[row+1]-a->i[row])*sizeof(PetscScalar));
128: /* right of diagonal part */
129: PetscMemcpy(b->a+b->i[row]+l,v+l+a->i[row+1]-a->i[row],(b->i[row+1]-b->i[row]-l)*sizeof(PetscScalar));
130: return(0);
131: }
135: PetscErrorCode MatSetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
136: {
137: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
138: PetscScalar value;
140: PetscInt i,j,rstart = mat->rmap.rstart,rend = mat->rmap.rend;
141: PetscInt cstart = mat->cmap.rstart,cend = mat->cmap.rend,row,col;
142: PetscTruth roworiented = aij->roworiented;
144: /* Some Variables required in the macro */
145: Mat A = aij->A;
146: Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data;
147: PetscInt *aimax = a->imax,*ai = a->i,*ailen = a->ilen,*aj = a->j;
148: PetscScalar *aa = a->a;
149: PetscTruth ignorezeroentries = (((a->ignorezeroentries)&&(addv==ADD_VALUES))?PETSC_TRUE:PETSC_FALSE);
150: Mat B = aij->B;
151: Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data;
152: PetscInt *bimax = b->imax,*bi = b->i,*bilen = b->ilen,*bj = b->j,bm = aij->B->rmap.n,am = aij->A->rmap.n;
153: PetscScalar *ba = b->a;
155: PetscInt *rp1,*rp2,ii,nrow1,nrow2,_i,rmax1,rmax2,N,low1,high1,low2,high2,t,lastcol1,lastcol2;
156: PetscInt nonew = a->nonew;
157: PetscScalar *ap1,*ap2;
160: for (i=0; i<m; i++) {
161: if (im[i] < 0) continue;
162: #if defined(PETSC_USE_DEBUG)
163: if (im[i] >= mat->rmap.N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap.N-1);
164: #endif
165: if (im[i] >= rstart && im[i] < rend) {
166: row = im[i] - rstart;
167: lastcol1 = -1;
168: rp1 = aj + ai[row];
169: ap1 = aa + ai[row];
170: rmax1 = aimax[row];
171: nrow1 = ailen[row];
172: low1 = 0;
173: high1 = nrow1;
174: lastcol2 = -1;
175: rp2 = bj + bi[row];
176: ap2 = ba + bi[row];
177: rmax2 = bimax[row];
178: nrow2 = bilen[row];
179: low2 = 0;
180: high2 = nrow2;
182: for (j=0; j<n; j++) {
183: if (roworiented) value = v[i*n+j]; else value = v[i+j*m];
184: if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue;
185: if (in[j] >= cstart && in[j] < cend){
186: col = in[j] - cstart;
187: MatSetValues_SeqAIJ_A_Private(row,col,value,addv);
188: } else if (in[j] < 0) continue;
189: #if defined(PETSC_USE_DEBUG)
190: else if (in[j] >= mat->cmap.N) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap.N-1);}
191: #endif
192: else {
193: if (mat->was_assembled) {
194: if (!aij->colmap) {
195: CreateColmap_MPIAIJ_Private(mat);
196: }
197: #if defined (PETSC_USE_CTABLE)
198: PetscTableFind(aij->colmap,in[j]+1,&col);
199: col--;
200: #else
201: col = aij->colmap[in[j]] - 1;
202: #endif
203: if (col < 0 && !((Mat_SeqAIJ*)(aij->A->data))->nonew) {
204: DisAssemble_MPIAIJ(mat);
205: col = in[j];
206: /* Reinitialize the variables required by MatSetValues_SeqAIJ_B_Private() */
207: B = aij->B;
208: b = (Mat_SeqAIJ*)B->data;
209: bimax = b->imax; bi = b->i; bilen = b->ilen; bj = b->j;
210: rp2 = bj + bi[row];
211: ap2 = ba + bi[row];
212: rmax2 = bimax[row];
213: nrow2 = bilen[row];
214: low2 = 0;
215: high2 = nrow2;
216: bm = aij->B->rmap.n;
217: ba = b->a;
218: }
219: } else col = in[j];
220: MatSetValues_SeqAIJ_B_Private(row,col,value,addv);
221: }
222: }
223: } else {
224: if (!aij->donotstash) {
225: if (roworiented) {
226: if (ignorezeroentries && v[i*n] == 0.0) continue;
227: MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n);
228: } else {
229: if (ignorezeroentries && v[i] == 0.0) continue;
230: MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m);
231: }
232: }
233: }
234: }
235: return(0);
236: }
240: PetscErrorCode MatGetValues_MPIAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
241: {
242: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
244: PetscInt i,j,rstart = mat->rmap.rstart,rend = mat->rmap.rend;
245: PetscInt cstart = mat->cmap.rstart,cend = mat->cmap.rend,row,col;
248: for (i=0; i<m; i++) {
249: if (idxm[i] < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);
250: if (idxm[i] >= mat->rmap.N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap.N-1);
251: if (idxm[i] >= rstart && idxm[i] < rend) {
252: row = idxm[i] - rstart;
253: for (j=0; j<n; j++) {
254: if (idxn[j] < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]);
255: if (idxn[j] >= mat->cmap.N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap.N-1);
256: if (idxn[j] >= cstart && idxn[j] < cend){
257: col = idxn[j] - cstart;
258: MatGetValues(aij->A,1,&row,1,&col,v+i*n+j);
259: } else {
260: if (!aij->colmap) {
261: CreateColmap_MPIAIJ_Private(mat);
262: }
263: #if defined (PETSC_USE_CTABLE)
264: PetscTableFind(aij->colmap,idxn[j]+1,&col);
265: col --;
266: #else
267: col = aij->colmap[idxn[j]] - 1;
268: #endif
269: if ((col < 0) || (aij->garray[col] != idxn[j])) *(v+i*n+j) = 0.0;
270: else {
271: MatGetValues(aij->B,1,&row,1,&col,v+i*n+j);
272: }
273: }
274: }
275: } else {
276: SETERRQ(PETSC_ERR_SUP,"Only local values currently supported");
277: }
278: }
279: return(0);
280: }
284: PetscErrorCode MatAssemblyBegin_MPIAIJ(Mat mat,MatAssemblyType mode)
285: {
286: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
288: PetscInt nstash,reallocs;
289: InsertMode addv;
292: if (aij->donotstash) {
293: return(0);
294: }
296: /* make sure all processors are either in INSERTMODE or ADDMODE */
297: MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,mat->comm);
298: if (addv == (ADD_VALUES|INSERT_VALUES)) {
299: SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added");
300: }
301: mat->insertmode = addv; /* in case this processor had no cache */
303: MatStashScatterBegin_Private(&mat->stash,mat->rmap.range);
304: MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
305: PetscInfo2(aij->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
306: return(0);
307: }
311: PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat mat,MatAssemblyType mode)
312: {
313: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
314: Mat_SeqAIJ *a=(Mat_SeqAIJ *)aij->A->data;
316: PetscMPIInt n;
317: PetscInt i,j,rstart,ncols,flg;
318: PetscInt *row,*col,other_disassembled;
319: PetscScalar *val;
320: InsertMode addv = mat->insertmode;
322: /* do not use 'b = (Mat_SeqAIJ *)aij->B->data' as B can be reset in disassembly */
324: if (!aij->donotstash) {
325: while (1) {
326: MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);
327: if (!flg) break;
329: for (i=0; i<n;) {
330: /* Now identify the consecutive vals belonging to the same row */
331: for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; }
332: if (j < n) ncols = j-i;
333: else ncols = n-i;
334: /* Now assemble all these values with a single function call */
335: MatSetValues_MPIAIJ(mat,1,row+i,ncols,col+i,val+i,addv);
336: i = j;
337: }
338: }
339: MatStashScatterEnd_Private(&mat->stash);
340: }
341: a->compressedrow.use = PETSC_FALSE;
342: MatAssemblyBegin(aij->A,mode);
343: MatAssemblyEnd(aij->A,mode);
345: /* determine if any processor has disassembled, if so we must
346: also disassemble ourselfs, in order that we may reassemble. */
347: /*
348: if nonzero structure of submatrix B cannot change then we know that
349: no processor disassembled thus we can skip this stuff
350: */
351: if (!((Mat_SeqAIJ*)aij->B->data)->nonew) {
352: MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,mat->comm);
353: if (mat->was_assembled && !other_disassembled) {
354: DisAssemble_MPIAIJ(mat);
355: }
356: }
357: if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
358: MatSetUpMultiply_MPIAIJ(mat);
359: }
360: MatSetOption(aij->B,MAT_DO_NOT_USE_INODES);
361: ((Mat_SeqAIJ *)aij->B->data)->compressedrow.use = PETSC_TRUE; /* b->compressedrow.use */
362: MatAssemblyBegin(aij->B,mode);
363: MatAssemblyEnd(aij->B,mode);
365: PetscFree(aij->rowvalues);
366: aij->rowvalues = 0;
368: /* used by MatAXPY() */
369: a->xtoy = 0; ((Mat_SeqAIJ *)aij->B->data)->xtoy = 0; /* b->xtoy = 0 */
370: a->XtoY = 0; ((Mat_SeqAIJ *)aij->B->data)->XtoY = 0; /* b->XtoY = 0 */
372: return(0);
373: }
377: PetscErrorCode MatZeroEntries_MPIAIJ(Mat A)
378: {
379: Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data;
383: MatZeroEntries(l->A);
384: MatZeroEntries(l->B);
385: return(0);
386: }
390: PetscErrorCode MatZeroRows_MPIAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag)
391: {
392: Mat_MPIAIJ *l = (Mat_MPIAIJ*)A->data;
394: PetscMPIInt size = l->size,imdex,n,rank = l->rank,tag = A->tag,lastidx = -1;
395: PetscInt i,*owners = A->rmap.range;
396: PetscInt *nprocs,j,idx,nsends,row;
397: PetscInt nmax,*svalues,*starts,*owner,nrecvs;
398: PetscInt *rvalues,count,base,slen,*source;
399: PetscInt *lens,*lrows,*values,rstart=A->rmap.rstart;
400: MPI_Comm comm = A->comm;
401: MPI_Request *send_waits,*recv_waits;
402: MPI_Status recv_status,*send_status;
403: #if defined(PETSC_DEBUG)
404: PetscTruth found = PETSC_FALSE;
405: #endif
408: /* first count number of contributors to each processor */
409: PetscMalloc(2*size*sizeof(PetscInt),&nprocs);
410: PetscMemzero(nprocs,2*size*sizeof(PetscInt));
411: PetscMalloc((N+1)*sizeof(PetscInt),&owner); /* see note*/
412: j = 0;
413: for (i=0; i<N; i++) {
414: if (lastidx > (idx = rows[i])) j = 0;
415: lastidx = idx;
416: for (; j<size; j++) {
417: if (idx >= owners[j] && idx < owners[j+1]) {
418: nprocs[2*j]++;
419: nprocs[2*j+1] = 1;
420: owner[i] = j;
421: #if defined(PETSC_DEBUG)
422: found = PETSC_TRUE;
423: #endif
424: break;
425: }
426: }
427: #if defined(PETSC_DEBUG)
428: if (!found) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Index out of range");
429: found = PETSC_FALSE;
430: #endif
431: }
432: nsends = 0; for (i=0; i<size; i++) { nsends += nprocs[2*i+1];}
434: /* inform other processors of number of messages and max length*/
435: PetscMaxSum(comm,nprocs,&nmax,&nrecvs);
437: /* post receives: */
438: PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);
439: PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);
440: for (i=0; i<nrecvs; i++) {
441: MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);
442: }
444: /* do sends:
445: 1) starts[i] gives the starting index in svalues for stuff going to
446: the ith processor
447: */
448: PetscMalloc((N+1)*sizeof(PetscInt),&svalues);
449: PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);
450: PetscMalloc((size+1)*sizeof(PetscInt),&starts);
451: starts[0] = 0;
452: for (i=1; i<size; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];}
453: for (i=0; i<N; i++) {
454: svalues[starts[owner[i]]++] = rows[i];
455: }
457: starts[0] = 0;
458: for (i=1; i<size+1; i++) { starts[i] = starts[i-1] + nprocs[2*i-2];}
459: count = 0;
460: for (i=0; i<size; i++) {
461: if (nprocs[2*i+1]) {
462: MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);
463: }
464: }
465: PetscFree(starts);
467: base = owners[rank];
469: /* wait on receives */
470: PetscMalloc(2*(nrecvs+1)*sizeof(PetscInt),&lens);
471: source = lens + nrecvs;
472: count = nrecvs; slen = 0;
473: while (count) {
474: MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);
475: /* unpack receives into our local space */
476: MPI_Get_count(&recv_status,MPIU_INT,&n);
477: source[imdex] = recv_status.MPI_SOURCE;
478: lens[imdex] = n;
479: slen += n;
480: count--;
481: }
482: PetscFree(recv_waits);
483:
484: /* move the data into the send scatter */
485: PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);
486: count = 0;
487: for (i=0; i<nrecvs; i++) {
488: values = rvalues + i*nmax;
489: for (j=0; j<lens[i]; j++) {
490: lrows[count++] = values[j] - base;
491: }
492: }
493: PetscFree(rvalues);
494: PetscFree(lens);
495: PetscFree(owner);
496: PetscFree(nprocs);
497:
498: /* actually zap the local rows */
499: /*
500: Zero the required rows. If the "diagonal block" of the matrix
501: is square and the user wishes to set the diagonal we use separate
502: code so that MatSetValues() is not called for each diagonal allocating
503: new memory, thus calling lots of mallocs and slowing things down.
505: Contributed by: Matthew Knepley
506: */
507: /* must zero l->B before l->A because the (diag) case below may put values into l->B*/
508: MatZeroRows(l->B,slen,lrows,0.0);
509: if ((diag != 0.0) && (l->A->rmap.N == l->A->cmap.N)) {
510: MatZeroRows(l->A,slen,lrows,diag);
511: } else if (diag != 0.0) {
512: MatZeroRows(l->A,slen,lrows,0.0);
513: if (((Mat_SeqAIJ*)l->A->data)->nonew) {
514: SETERRQ(PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options\n\
515: MAT_NO_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR");
516: }
517: for (i = 0; i < slen; i++) {
518: row = lrows[i] + rstart;
519: MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);
520: }
521: MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
522: MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
523: } else {
524: MatZeroRows(l->A,slen,lrows,0.0);
525: }
526: PetscFree(lrows);
528: /* wait on sends */
529: if (nsends) {
530: PetscMalloc(nsends*sizeof(MPI_Status),&send_status);
531: MPI_Waitall(nsends,send_waits,send_status);
532: PetscFree(send_status);
533: }
534: PetscFree(send_waits);
535: PetscFree(svalues);
537: return(0);
538: }
542: PetscErrorCode MatMult_MPIAIJ(Mat A,Vec xx,Vec yy)
543: {
544: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
546: PetscInt nt;
549: VecGetLocalSize(xx,&nt);
550: if (nt != A->cmap.n) {
551: SETERRQ2(PETSC_ERR_ARG_SIZ,"Incompatible partition of A (%D) and xx (%D)",A->cmap.n,nt);
552: }
553: VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
554: (*a->A->ops->mult)(a->A,xx,yy);
555: VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
556: (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
557: return(0);
558: }
562: PetscErrorCode MatMultAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz)
563: {
564: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
568: VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
569: (*a->A->ops->multadd)(a->A,xx,yy,zz);
570: VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
571: (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);
572: return(0);
573: }
577: PetscErrorCode MatMultTranspose_MPIAIJ(Mat A,Vec xx,Vec yy)
578: {
579: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
581: PetscTruth merged;
584: VecScatterGetMerged(a->Mvctx,&merged);
585: /* do nondiagonal part */
586: (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
587: if (!merged) {
588: /* send it on its way */
589: VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
590: /* do local part */
591: (*a->A->ops->multtranspose)(a->A,xx,yy);
592: /* receive remote parts: note this assumes the values are not actually */
593: /* added in yy until the next line, */
594: VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
595: } else {
596: /* do local part */
597: (*a->A->ops->multtranspose)(a->A,xx,yy);
598: /* send it on its way */
599: VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
600: /* values actually were received in the Begin() but we need to call this nop */
601: VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
602: }
603: return(0);
604: }
609: PetscErrorCode MatIsTranspose_MPIAIJ(Mat Amat,Mat Bmat,PetscReal tol,PetscTruth *f)
610: {
611: MPI_Comm comm;
612: Mat_MPIAIJ *Aij = (Mat_MPIAIJ *) Amat->data, *Bij;
613: Mat Adia = Aij->A, Bdia, Aoff,Boff,*Aoffs,*Boffs;
614: IS Me,Notme;
616: PetscInt M,N,first,last,*notme,i;
617: PetscMPIInt size;
621: /* Easy test: symmetric diagonal block */
622: Bij = (Mat_MPIAIJ *) Bmat->data; Bdia = Bij->A;
623: MatIsTranspose(Adia,Bdia,tol,f);
624: if (!*f) return(0);
625: PetscObjectGetComm((PetscObject)Amat,&comm);
626: MPI_Comm_size(comm,&size);
627: if (size == 1) return(0);
629: /* Hard test: off-diagonal block. This takes a MatGetSubMatrix. */
630: MatGetSize(Amat,&M,&N);
631: MatGetOwnershipRange(Amat,&first,&last);
632: PetscMalloc((N-last+first)*sizeof(PetscInt),¬me);
633: for (i=0; i<first; i++) notme[i] = i;
634: for (i=last; i<M; i++) notme[i-last+first] = i;
635: ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,&Notme);
636: ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);
637: MatGetSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);
638: Aoff = Aoffs[0];
639: MatGetSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);
640: Boff = Boffs[0];
641: MatIsTranspose(Aoff,Boff,tol,f);
642: MatDestroyMatrices(1,&Aoffs);
643: MatDestroyMatrices(1,&Boffs);
644: ISDestroy(Me);
645: ISDestroy(Notme);
647: return(0);
648: }
653: PetscErrorCode MatMultTransposeAdd_MPIAIJ(Mat A,Vec xx,Vec yy,Vec zz)
654: {
655: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
659: /* do nondiagonal part */
660: (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
661: /* send it on its way */
662: VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
663: /* do local part */
664: (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);
665: /* receive remote parts */
666: VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
667: return(0);
668: }
670: /*
671: This only works correctly for square matrices where the subblock A->A is the
672: diagonal block
673: */
676: PetscErrorCode MatGetDiagonal_MPIAIJ(Mat A,Vec v)
677: {
679: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
682: if (A->rmap.N != A->cmap.N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block");
683: if (A->rmap.rstart != A->cmap.rstart || A->rmap.rend != A->cmap.rend) {
684: SETERRQ(PETSC_ERR_ARG_SIZ,"row partition must equal col partition");
685: }
686: MatGetDiagonal(a->A,v);
687: return(0);
688: }
692: PetscErrorCode MatScale_MPIAIJ(Mat A,PetscScalar aa)
693: {
694: Mat_MPIAIJ *a = (Mat_MPIAIJ*)A->data;
698: MatScale(a->A,aa);
699: MatScale(a->B,aa);
700: return(0);
701: }
705: PetscErrorCode MatDestroy_MPIAIJ(Mat mat)
706: {
707: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
711: #if defined(PETSC_USE_LOG)
712: PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap.N,mat->cmap.N);
713: #endif
714: MatStashDestroy_Private(&mat->stash);
715: MatDestroy(aij->A);
716: MatDestroy(aij->B);
717: #if defined (PETSC_USE_CTABLE)
718: if (aij->colmap) {PetscTableDestroy(aij->colmap);}
719: #else
720: PetscFree(aij->colmap);
721: #endif
722: PetscFree(aij->garray);
723: if (aij->lvec) {VecDestroy(aij->lvec);}
724: if (aij->Mvctx) {VecScatterDestroy(aij->Mvctx);}
725: PetscFree(aij->rowvalues);
726: PetscFree(aij->ld);
727: PetscFree(aij);
729: PetscObjectChangeTypeName((PetscObject)mat,0);
730: PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C","",PETSC_NULL);
731: PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C","",PETSC_NULL);
732: PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",PETSC_NULL);
733: PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C","",PETSC_NULL);
734: PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocation_C","",PETSC_NULL);
735: PetscObjectComposeFunction((PetscObject)mat,"MatMPIAIJSetPreallocationCSR_C","",PETSC_NULL);
736: PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C","",PETSC_NULL);
737: return(0);
738: }
742: PetscErrorCode MatView_MPIAIJ_Binary(Mat mat,PetscViewer viewer)
743: {
744: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
745: Mat_SeqAIJ* A = (Mat_SeqAIJ*)aij->A->data;
746: Mat_SeqAIJ* B = (Mat_SeqAIJ*)aij->B->data;
747: PetscErrorCode ierr;
748: PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag;
749: int fd;
750: PetscInt nz,header[4],*row_lengths,*range=0,rlen,i;
751: PetscInt nzmax,*column_indices,j,k,col,*garray = aij->garray,cnt,cstart = mat->cmap.rstart,rnz;
752: PetscScalar *column_values;
755: MPI_Comm_rank(mat->comm,&rank);
756: MPI_Comm_size(mat->comm,&size);
757: nz = A->nz + B->nz;
758: if (!rank) {
759: header[0] = MAT_FILE_COOKIE;
760: header[1] = mat->rmap.N;
761: header[2] = mat->cmap.N;
762: MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,mat->comm);
763: PetscViewerBinaryGetDescriptor(viewer,&fd);
764: PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);
765: /* get largest number of rows any processor has */
766: rlen = mat->rmap.n;
767: range = mat->rmap.range;
768: for (i=1; i<size; i++) {
769: rlen = PetscMax(rlen,range[i+1] - range[i]);
770: }
771: } else {
772: MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,mat->comm);
773: rlen = mat->rmap.n;
774: }
776: /* load up the local row counts */
777: PetscMalloc((rlen+1)*sizeof(PetscInt),&row_lengths);
778: for (i=0; i<mat->rmap.n; i++) {
779: row_lengths[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i];
780: }
782: /* store the row lengths to the file */
783: if (!rank) {
784: MPI_Status status;
785: PetscBinaryWrite(fd,row_lengths,mat->rmap.n,PETSC_INT,PETSC_TRUE);
786: for (i=1; i<size; i++) {
787: rlen = range[i+1] - range[i];
788: MPI_Recv(row_lengths,rlen,MPIU_INT,i,tag,mat->comm,&status);
789: PetscBinaryWrite(fd,row_lengths,rlen,PETSC_INT,PETSC_TRUE);
790: }
791: } else {
792: MPI_Send(row_lengths,mat->rmap.n,MPIU_INT,0,tag,mat->comm);
793: }
794: PetscFree(row_lengths);
796: /* load up the local column indices */
797: nzmax = nz; /* )th processor needs space a largest processor needs */
798: MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,mat->comm);
799: PetscMalloc((nzmax+1)*sizeof(PetscInt),&column_indices);
800: cnt = 0;
801: for (i=0; i<mat->rmap.n; i++) {
802: for (j=B->i[i]; j<B->i[i+1]; j++) {
803: if ( (col = garray[B->j[j]]) > cstart) break;
804: column_indices[cnt++] = col;
805: }
806: for (k=A->i[i]; k<A->i[i+1]; k++) {
807: column_indices[cnt++] = A->j[k] + cstart;
808: }
809: for (; j<B->i[i+1]; j++) {
810: column_indices[cnt++] = garray[B->j[j]];
811: }
812: }
813: if (cnt != A->nz + B->nz) SETERRQ2(PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz);
815: /* store the column indices to the file */
816: if (!rank) {
817: MPI_Status status;
818: PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);
819: for (i=1; i<size; i++) {
820: MPI_Recv(&rnz,1,MPIU_INT,i,tag,mat->comm,&status);
821: if (rnz > nzmax) SETERRQ2(PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax);
822: MPI_Recv(column_indices,rnz,MPIU_INT,i,tag,mat->comm,&status);
823: PetscBinaryWrite(fd,column_indices,rnz,PETSC_INT,PETSC_TRUE);
824: }
825: } else {
826: MPI_Send(&nz,1,MPIU_INT,0,tag,mat->comm);
827: MPI_Send(column_indices,nz,MPIU_INT,0,tag,mat->comm);
828: }
829: PetscFree(column_indices);
831: /* load up the local column values */
832: PetscMalloc((nzmax+1)*sizeof(PetscScalar),&column_values);
833: cnt = 0;
834: for (i=0; i<mat->rmap.n; i++) {
835: for (j=B->i[i]; j<B->i[i+1]; j++) {
836: if ( garray[B->j[j]] > cstart) break;
837: column_values[cnt++] = B->a[j];
838: }
839: for (k=A->i[i]; k<A->i[i+1]; k++) {
840: column_values[cnt++] = A->a[k];
841: }
842: for (; j<B->i[i+1]; j++) {
843: column_values[cnt++] = B->a[j];
844: }
845: }
846: if (cnt != A->nz + B->nz) SETERRQ2(PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,A->nz+B->nz);
848: /* store the column values to the file */
849: if (!rank) {
850: MPI_Status status;
851: PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);
852: for (i=1; i<size; i++) {
853: MPI_Recv(&rnz,1,MPIU_INT,i,tag,mat->comm,&status);
854: if (rnz > nzmax) SETERRQ2(PETSC_ERR_LIB,"Internal PETSc error: nz = %D nzmax = %D",nz,nzmax);
855: MPI_Recv(column_values,rnz,MPIU_SCALAR,i,tag,mat->comm,&status);
856: PetscBinaryWrite(fd,column_values,rnz,PETSC_SCALAR,PETSC_TRUE);
857: }
858: } else {
859: MPI_Send(&nz,1,MPIU_INT,0,tag,mat->comm);
860: MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,mat->comm);
861: }
862: PetscFree(column_values);
863: return(0);
864: }
868: PetscErrorCode MatView_MPIAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
869: {
870: Mat_MPIAIJ *aij = (Mat_MPIAIJ*)mat->data;
871: PetscErrorCode ierr;
872: PetscMPIInt rank = aij->rank,size = aij->size;
873: PetscTruth isdraw,iascii,isbinary;
874: PetscViewer sviewer;
875: PetscViewerFormat format;
878: PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);
879: PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);
880: PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);
881: if (iascii) {
882: PetscViewerGetFormat(viewer,&format);
883: if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
884: MatInfo info;
885: PetscTruth inodes;
887: MPI_Comm_rank(mat->comm,&rank);
888: MatGetInfo(mat,MAT_LOCAL,&info);
889: MatInodeGetInodeSizes(aij->A,PETSC_NULL,(PetscInt **)&inodes,PETSC_NULL);
890: if (!inodes) {
891: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n",
892: rank,mat->rmap.n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);
893: } else {
894: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n",
895: rank,mat->rmap.n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);
896: }
897: MatGetInfo(aij->A,MAT_LOCAL,&info);
898: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
899: MatGetInfo(aij->B,MAT_LOCAL,&info);
900: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
901: PetscViewerFlush(viewer);
902: PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
903: VecScatterView(aij->Mvctx,viewer);
904: return(0);
905: } else if (format == PETSC_VIEWER_ASCII_INFO) {
906: PetscInt inodecount,inodelimit,*inodes;
907: MatInodeGetInodeSizes(aij->A,&inodecount,&inodes,&inodelimit);
908: if (inodes) {
909: PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);
910: } else {
911: PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");
912: }
913: return(0);
914: } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
915: return(0);
916: }
917: } else if (isbinary) {
918: if (size == 1) {
919: PetscObjectSetName((PetscObject)aij->A,mat->name);
920: MatView(aij->A,viewer);
921: } else {
922: MatView_MPIAIJ_Binary(mat,viewer);
923: }
924: return(0);
925: } else if (isdraw) {
926: PetscDraw draw;
927: PetscTruth isnull;
928: PetscViewerDrawGetDraw(viewer,0,&draw);
929: PetscDrawIsNull(draw,&isnull); if (isnull) return(0);
930: }
932: if (size == 1) {
933: PetscObjectSetName((PetscObject)aij->A,mat->name);
934: MatView(aij->A,viewer);
935: } else {
936: /* assemble the entire matrix onto first processor. */
937: Mat A;
938: Mat_SeqAIJ *Aloc;
939: PetscInt M = mat->rmap.N,N = mat->cmap.N,m,*ai,*aj,row,*cols,i,*ct;
940: PetscScalar *a;
942: MatCreate(mat->comm,&A);
943: if (!rank) {
944: MatSetSizes(A,M,N,M,N);
945: } else {
946: MatSetSizes(A,0,0,M,N);
947: }
948: /* This is just a temporary matrix, so explicitly using MATMPIAIJ is probably best */
949: MatSetType(A,MATMPIAIJ);
950: MatMPIAIJSetPreallocation(A,0,PETSC_NULL,0,PETSC_NULL);
951: PetscLogObjectParent(mat,A);
953: /* copy over the A part */
954: Aloc = (Mat_SeqAIJ*)aij->A->data;
955: m = aij->A->rmap.n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a;
956: row = mat->rmap.rstart;
957: for (i=0; i<ai[m]; i++) {aj[i] += mat->cmap.rstart ;}
958: for (i=0; i<m; i++) {
959: MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,INSERT_VALUES);
960: row++; a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i];
961: }
962: aj = Aloc->j;
963: for (i=0; i<ai[m]; i++) {aj[i] -= mat->cmap.rstart;}
965: /* copy over the B part */
966: Aloc = (Mat_SeqAIJ*)aij->B->data;
967: m = aij->B->rmap.n; ai = Aloc->i; aj = Aloc->j; a = Aloc->a;
968: row = mat->rmap.rstart;
969: PetscMalloc((ai[m]+1)*sizeof(PetscInt),&cols);
970: ct = cols;
971: for (i=0; i<ai[m]; i++) {cols[i] = aij->garray[aj[i]];}
972: for (i=0; i<m; i++) {
973: MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,INSERT_VALUES);
974: row++; a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i];
975: }
976: PetscFree(ct);
977: MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
978: MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
979: /*
980: Everyone has to call to draw the matrix since the graphics waits are
981: synchronized across all processors that share the PetscDraw object
982: */
983: PetscViewerGetSingleton(viewer,&sviewer);
984: if (!rank) {
985: PetscObjectSetName((PetscObject)((Mat_MPIAIJ*)(A->data))->A,mat->name);
986: MatView(((Mat_MPIAIJ*)(A->data))->A,sviewer);
987: }
988: PetscViewerRestoreSingleton(viewer,&sviewer);
989: MatDestroy(A);
990: }
991: return(0);
992: }
996: PetscErrorCode MatView_MPIAIJ(Mat mat,PetscViewer viewer)
997: {
999: PetscTruth iascii,isdraw,issocket,isbinary;
1000:
1002: PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);
1003: PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);
1004: PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);
1005: PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);
1006: if (iascii || isdraw || isbinary || issocket) {
1007: MatView_MPIAIJ_ASCIIorDraworSocket(mat,viewer);
1008: } else {
1009: SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported by MPIAIJ matrices",((PetscObject)viewer)->type_name);
1010: }
1011: return(0);
1012: }
1016: PetscErrorCode MatRelax_MPIAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
1017: {
1018: Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data;
1020: Vec bb1;
1023: if (its <= 0 || lits <= 0) SETERRQ2(PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
1025: VecDuplicate(bb,&bb1);
1027: if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){
1028: if (flag & SOR_ZERO_INITIAL_GUESS) {
1029: (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,lits,xx);
1030: its--;
1031: }
1032:
1033: while (its--) {
1034: VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1035: VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1037: /* update rhs: bb1 = bb - B*x */
1038: VecScale(mat->lvec,-1.0);
1039: (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);
1041: /* local sweep */
1042: (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);
1043:
1044: }
1045: } else if (flag & SOR_LOCAL_FORWARD_SWEEP){
1046: if (flag & SOR_ZERO_INITIAL_GUESS) {
1047: (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,PETSC_NULL,xx);
1048: its--;
1049: }
1050: while (its--) {
1051: VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1052: VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1054: /* update rhs: bb1 = bb - B*x */
1055: VecScale(mat->lvec,-1.0);
1056: (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);
1058: /* local sweep */
1059: (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,PETSC_NULL,xx);
1060:
1061: }
1062: } else if (flag & SOR_LOCAL_BACKWARD_SWEEP){
1063: if (flag & SOR_ZERO_INITIAL_GUESS) {
1064: (*mat->A->ops->relax)(mat->A,bb,omega,flag,fshift,lits,PETSC_NULL,xx);
1065: its--;
1066: }
1067: while (its--) {
1068: VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1069: VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
1071: /* update rhs: bb1 = bb - B*x */
1072: VecScale(mat->lvec,-1.0);
1073: (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);
1075: /* local sweep */
1076: (*mat->A->ops->relax)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,PETSC_NULL,xx);
1077:
1078: }
1079: } else {
1080: SETERRQ(PETSC_ERR_SUP,"Parallel SOR not supported");
1081: }
1083: VecDestroy(bb1);
1084: return(0);
1085: }
1089: PetscErrorCode MatPermute_MPIAIJ(Mat A,IS rowp,IS colp,Mat *B)
1090: {
1091: MPI_Comm comm,pcomm;
1092: PetscInt first,local_size,nrows,*rows;
1093: int ntids;
1094: IS crowp,growp,irowp,lrowp,lcolp,icolp;
1098: PetscObjectGetComm((PetscObject)A,&comm);
1099: /* make a collective version of 'rowp' */
1100: PetscObjectGetComm((PetscObject)rowp,&pcomm);
1101: if (pcomm==comm) {
1102: crowp = rowp;
1103: } else {
1104: ISGetSize(rowp,&nrows);
1105: ISGetIndices(rowp,&rows);
1106: ISCreateGeneral(comm,nrows,rows,&crowp);
1107: ISRestoreIndices(rowp,&rows);
1108: }
1109: /* collect the global row permutation and invert it */
1110: ISAllGather(crowp,&growp);
1111: ISSetPermutation(growp);
1112: if (pcomm!=comm) {
1113: ISDestroy(crowp);
1114: }
1115: ISInvertPermutation(growp,PETSC_DECIDE,&irowp);
1116: /* get the local target indices */
1117: MatGetOwnershipRange(A,&first,PETSC_NULL);
1118: MatGetLocalSize(A,&local_size,PETSC_NULL);
1119: ISGetIndices(irowp,&rows);
1120: ISCreateGeneral(MPI_COMM_SELF,local_size,rows+first,&lrowp);
1121: ISRestoreIndices(irowp,&rows);
1122: ISDestroy(irowp);
1123: /* the column permutation is so much easier;
1124: make a local version of 'colp' and invert it */
1125: PetscObjectGetComm((PetscObject)colp,&pcomm);
1126: MPI_Comm_size(pcomm,&ntids);
1127: if (ntids==1) {
1128: lcolp = colp;
1129: } else {
1130: ISGetSize(colp,&nrows);
1131: ISGetIndices(colp,&rows);
1132: ISCreateGeneral(MPI_COMM_SELF,nrows,rows,&lcolp);
1133: }
1134: ISInvertPermutation(lcolp,PETSC_DECIDE,&icolp);
1135: ISSetPermutation(lcolp);
1136: if (ntids>1) {
1137: ISRestoreIndices(colp,&rows);
1138: ISDestroy(lcolp);
1139: }
1140: /* now we just get the submatrix */
1141: MatGetSubMatrix(A,lrowp,icolp,local_size,MAT_INITIAL_MATRIX,B);
1142: /* clean up */
1143: ISDestroy(lrowp);
1144: ISDestroy(icolp);
1145: return(0);
1146: }
1150: PetscErrorCode MatGetInfo_MPIAIJ(Mat matin,MatInfoType flag,MatInfo *info)
1151: {
1152: Mat_MPIAIJ *mat = (Mat_MPIAIJ*)matin->data;
1153: Mat A = mat->A,B = mat->B;
1155: PetscReal isend[5],irecv[5];
1158: info->block_size = 1.0;
1159: MatGetInfo(A,MAT_LOCAL,info);
1160: isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
1161: isend[3] = info->memory; isend[4] = info->mallocs;
1162: MatGetInfo(B,MAT_LOCAL,info);
1163: isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
1164: isend[3] += info->memory; isend[4] += info->mallocs;
1165: if (flag == MAT_LOCAL) {
1166: info->nz_used = isend[0];
1167: info->nz_allocated = isend[1];
1168: info->nz_unneeded = isend[2];
1169: info->memory = isend[3];
1170: info->mallocs = isend[4];
1171: } else if (flag == MAT_GLOBAL_MAX) {
1172: MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,matin->comm);
1173: info->nz_used = irecv[0];
1174: info->nz_allocated = irecv[1];
1175: info->nz_unneeded = irecv[2];
1176: info->memory = irecv[3];
1177: info->mallocs = irecv[4];
1178: } else if (flag == MAT_GLOBAL_SUM) {
1179: MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_SUM,matin->comm);