Actual source code: mpisbaij.c
petsc-3.9.4 2018-09-11
2: #include <../src/mat/impls/baij/mpi/mpibaij.h>
3: #include <../src/mat/impls/sbaij/mpi/mpisbaij.h>
4: #include <../src/mat/impls/sbaij/seq/sbaij.h>
5: #include <petscblaslapack.h>
7: #if defined(PETSC_HAVE_ELEMENTAL)
8: PETSC_INTERN PetscErrorCode MatConvert_MPISBAIJ_Elemental(Mat,MatType,MatReuse,Mat*);
9: #endif
10: PetscErrorCode MatStoreValues_MPISBAIJ(Mat mat)
11: {
12: Mat_MPISBAIJ *aij = (Mat_MPISBAIJ*)mat->data;
16: MatStoreValues(aij->A);
17: MatStoreValues(aij->B);
18: return(0);
19: }
21: PetscErrorCode MatRetrieveValues_MPISBAIJ(Mat mat)
22: {
23: Mat_MPISBAIJ *aij = (Mat_MPISBAIJ*)mat->data;
27: MatRetrieveValues(aij->A);
28: MatRetrieveValues(aij->B);
29: return(0);
30: }
32: #define MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv,orow,ocol) \
33: { \
34: \
35: brow = row/bs; \
36: rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \
37: rmax = aimax[brow]; nrow = ailen[brow]; \
38: bcol = col/bs; \
39: ridx = row % bs; cidx = col % bs; \
40: low = 0; high = nrow; \
41: while (high-low > 3) { \
42: t = (low+high)/2; \
43: if (rp[t] > bcol) high = t; \
44: else low = t; \
45: } \
46: for (_i=low; _i<high; _i++) { \
47: if (rp[_i] > bcol) break; \
48: if (rp[_i] == bcol) { \
49: bap = ap + bs2*_i + bs*cidx + ridx; \
50: if (addv == ADD_VALUES) *bap += value; \
51: else *bap = value; \
52: goto a_noinsert; \
53: } \
54: } \
55: if (a->nonew == 1) goto a_noinsert; \
56: if (a->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \
57: MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \
58: N = nrow++ - 1; \
59: /* shift up all the later entries in this row */ \
60: for (ii=N; ii>=_i; ii--) { \
61: rp[ii+1] = rp[ii]; \
62: PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar)); \
63: } \
64: if (N>=_i) { PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar)); } \
65: rp[_i] = bcol; \
66: ap[bs2*_i + bs*cidx + ridx] = value; \
67: A->nonzerostate++;\
68: a_noinsert:; \
69: ailen[brow] = nrow; \
70: }
72: #define MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv,orow,ocol) \
73: { \
74: brow = row/bs; \
75: rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \
76: rmax = bimax[brow]; nrow = bilen[brow]; \
77: bcol = col/bs; \
78: ridx = row % bs; cidx = col % bs; \
79: low = 0; high = nrow; \
80: while (high-low > 3) { \
81: t = (low+high)/2; \
82: if (rp[t] > bcol) high = t; \
83: else low = t; \
84: } \
85: for (_i=low; _i<high; _i++) { \
86: if (rp[_i] > bcol) break; \
87: if (rp[_i] == bcol) { \
88: bap = ap + bs2*_i + bs*cidx + ridx; \
89: if (addv == ADD_VALUES) *bap += value; \
90: else *bap = value; \
91: goto b_noinsert; \
92: } \
93: } \
94: if (b->nonew == 1) goto b_noinsert; \
95: if (b->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \
96: MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \
97: N = nrow++ - 1; \
98: /* shift up all the later entries in this row */ \
99: for (ii=N; ii>=_i; ii--) { \
100: rp[ii+1] = rp[ii]; \
101: PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar)); \
102: } \
103: if (N>=_i) { PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));} \
104: rp[_i] = bcol; \
105: ap[bs2*_i + bs*cidx + ridx] = value; \
106: B->nonzerostate++;\
107: b_noinsert:; \
108: bilen[brow] = nrow; \
109: }
111: /* Only add/insert a(i,j) with i<=j (blocks).
112: Any a(i,j) with i>j input by user is ingored.
113: */
114: PetscErrorCode MatSetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
115: {
116: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
117: MatScalar value;
118: PetscBool roworiented = baij->roworiented;
120: PetscInt i,j,row,col;
121: PetscInt rstart_orig=mat->rmap->rstart;
122: PetscInt rend_orig =mat->rmap->rend,cstart_orig=mat->cmap->rstart;
123: PetscInt cend_orig =mat->cmap->rend,bs=mat->rmap->bs;
125: /* Some Variables required in the macro */
126: Mat A = baij->A;
127: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)(A)->data;
128: PetscInt *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j;
129: MatScalar *aa =a->a;
131: Mat B = baij->B;
132: Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data;
133: PetscInt *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j;
134: MatScalar *ba =b->a;
136: PetscInt *rp,ii,nrow,_i,rmax,N,brow,bcol;
137: PetscInt low,high,t,ridx,cidx,bs2=a->bs2;
138: MatScalar *ap,*bap;
140: /* for stash */
141: PetscInt n_loc, *in_loc = NULL;
142: MatScalar *v_loc = NULL;
145: if (!baij->donotstash) {
146: if (n > baij->n_loc) {
147: PetscFree(baij->in_loc);
148: PetscFree(baij->v_loc);
149: PetscMalloc1(n,&baij->in_loc);
150: PetscMalloc1(n,&baij->v_loc);
152: baij->n_loc = n;
153: }
154: in_loc = baij->in_loc;
155: v_loc = baij->v_loc;
156: }
158: for (i=0; i<m; i++) {
159: if (im[i] < 0) continue;
160: #if defined(PETSC_USE_DEBUG)
161: 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);
162: #endif
163: if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */
164: row = im[i] - rstart_orig; /* local row index */
165: for (j=0; j<n; j++) {
166: if (im[i]/bs > in[j]/bs) {
167: if (a->ignore_ltriangular) {
168: continue; /* ignore lower triangular blocks */
169: } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_USER,"Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)");
170: }
171: if (in[j] >= cstart_orig && in[j] < cend_orig) { /* diag entry (A) */
172: col = in[j] - cstart_orig; /* local col index */
173: brow = row/bs; bcol = col/bs;
174: if (brow > bcol) continue; /* ignore lower triangular blocks of A */
175: if (roworiented) value = v[i*n+j];
176: else value = v[i+j*m];
177: MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv,im[i],in[j]);
178: /* MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv); */
179: } else if (in[j] < 0) continue;
180: #if defined(PETSC_USE_DEBUG)
181: 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);
182: #endif
183: else { /* off-diag entry (B) */
184: if (mat->was_assembled) {
185: if (!baij->colmap) {
186: MatCreateColmap_MPIBAIJ_Private(mat);
187: }
188: #if defined(PETSC_USE_CTABLE)
189: PetscTableFind(baij->colmap,in[j]/bs + 1,&col);
190: col = col - 1;
191: #else
192: col = baij->colmap[in[j]/bs] - 1;
193: #endif
194: if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) {
195: MatDisAssemble_MPISBAIJ(mat);
196: col = in[j];
197: /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */
198: B = baij->B;
199: b = (Mat_SeqBAIJ*)(B)->data;
200: bimax= b->imax;bi=b->i;bilen=b->ilen;bj=b->j;
201: ba = b->a;
202: } else col += in[j]%bs;
203: } else col = in[j];
204: if (roworiented) value = v[i*n+j];
205: else value = v[i+j*m];
206: MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv,im[i],in[j]);
207: /* MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv); */
208: }
209: }
210: } else { /* off processor entry */
211: 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]);
212: if (!baij->donotstash) {
213: mat->assembled = PETSC_FALSE;
214: n_loc = 0;
215: for (j=0; j<n; j++) {
216: if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */
217: in_loc[n_loc] = in[j];
218: if (roworiented) {
219: v_loc[n_loc] = v[i*n+j];
220: } else {
221: v_loc[n_loc] = v[j*m+i];
222: }
223: n_loc++;
224: }
225: MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc,PETSC_FALSE);
226: }
227: }
228: }
229: return(0);
230: }
232: PETSC_STATIC_INLINE PetscErrorCode MatSetValuesBlocked_SeqSBAIJ_Inlined(Mat A,PetscInt row,PetscInt col,const PetscScalar v[],InsertMode is,PetscInt orow,PetscInt ocol)
233: {
234: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data;
235: PetscErrorCode ierr;
236: PetscInt *rp,low,high,t,ii,jj,nrow,i,rmax,N;
237: PetscInt *imax =a->imax,*ai=a->i,*ailen=a->ilen;
238: PetscInt *aj =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs;
239: PetscBool roworiented=a->roworiented;
240: const PetscScalar *value = v;
241: MatScalar *ap,*aa = a->a,*bap;
244: if (col < row) {
245: if (a->ignore_ltriangular) return(0); /* ignore lower triangular block */
246: else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_USER,"Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)");
247: }
248: rp = aj + ai[row];
249: ap = aa + bs2*ai[row];
250: rmax = imax[row];
251: nrow = ailen[row];
252: value = v;
253: low = 0;
254: high = nrow;
256: while (high-low > 7) {
257: t = (low+high)/2;
258: if (rp[t] > col) high = t;
259: else low = t;
260: }
261: for (i=low; i<high; i++) {
262: if (rp[i] > col) break;
263: if (rp[i] == col) {
264: bap = ap + bs2*i;
265: if (roworiented) {
266: if (is == ADD_VALUES) {
267: for (ii=0; ii<bs; ii++) {
268: for (jj=ii; jj<bs2; jj+=bs) {
269: bap[jj] += *value++;
270: }
271: }
272: } else {
273: for (ii=0; ii<bs; ii++) {
274: for (jj=ii; jj<bs2; jj+=bs) {
275: bap[jj] = *value++;
276: }
277: }
278: }
279: } else {
280: if (is == ADD_VALUES) {
281: for (ii=0; ii<bs; ii++) {
282: for (jj=0; jj<bs; jj++) {
283: *bap++ += *value++;
284: }
285: }
286: } else {
287: for (ii=0; ii<bs; ii++) {
288: for (jj=0; jj<bs; jj++) {
289: *bap++ = *value++;
290: }
291: }
292: }
293: }
294: goto noinsert2;
295: }
296: }
297: if (nonew == 1) goto noinsert2;
298: if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new block index nonzero block (%D, %D) in the matrix", orow, ocol);
299: MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
300: N = nrow++ - 1; high++;
301: /* shift up all the later entries in this row */
302: for (ii=N; ii>=i; ii--) {
303: rp[ii+1] = rp[ii];
304: PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));
305: }
306: if (N >= i) {
307: PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));
308: }
309: rp[i] = col;
310: bap = ap + bs2*i;
311: if (roworiented) {
312: for (ii=0; ii<bs; ii++) {
313: for (jj=ii; jj<bs2; jj+=bs) {
314: bap[jj] = *value++;
315: }
316: }
317: } else {
318: for (ii=0; ii<bs; ii++) {
319: for (jj=0; jj<bs; jj++) {
320: *bap++ = *value++;
321: }
322: }
323: }
324: noinsert2:;
325: ailen[row] = nrow;
326: return(0);
327: }
329: /*
330: This routine is exactly duplicated in mpibaij.c
331: */
332: PETSC_STATIC_INLINE PetscErrorCode MatSetValuesBlocked_SeqBAIJ_Inlined(Mat A,PetscInt row,PetscInt col,const PetscScalar v[],InsertMode is,PetscInt orow,PetscInt ocol)
333: {
334: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
335: PetscInt *rp,low,high,t,ii,jj,nrow,i,rmax,N;
336: PetscInt *imax=a->imax,*ai=a->i,*ailen=a->ilen;
337: PetscErrorCode ierr;
338: PetscInt *aj =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs;
339: PetscBool roworiented=a->roworiented;
340: const PetscScalar *value = v;
341: MatScalar *ap,*aa = a->a,*bap;
344: rp = aj + ai[row];
345: ap = aa + bs2*ai[row];
346: rmax = imax[row];
347: nrow = ailen[row];
348: low = 0;
349: high = nrow;
350: value = v;
351: while (high-low > 7) {
352: t = (low+high)/2;
353: if (rp[t] > col) high = t;
354: else low = t;
355: }
356: for (i=low; i<high; i++) {
357: if (rp[i] > col) break;
358: if (rp[i] == col) {
359: bap = ap + bs2*i;
360: if (roworiented) {
361: if (is == ADD_VALUES) {
362: for (ii=0; ii<bs; ii++) {
363: for (jj=ii; jj<bs2; jj+=bs) {
364: bap[jj] += *value++;
365: }
366: }
367: } else {
368: for (ii=0; ii<bs; ii++) {
369: for (jj=ii; jj<bs2; jj+=bs) {
370: bap[jj] = *value++;
371: }
372: }
373: }
374: } else {
375: if (is == ADD_VALUES) {
376: for (ii=0; ii<bs; ii++,value+=bs) {
377: for (jj=0; jj<bs; jj++) {
378: bap[jj] += value[jj];
379: }
380: bap += bs;
381: }
382: } else {
383: for (ii=0; ii<bs; ii++,value+=bs) {
384: for (jj=0; jj<bs; jj++) {
385: bap[jj] = value[jj];
386: }
387: bap += bs;
388: }
389: }
390: }
391: goto noinsert2;
392: }
393: }
394: if (nonew == 1) goto noinsert2;
395: if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new global block indexed nonzero block (%D, %D) in the matrix", orow, ocol);
396: MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
397: N = nrow++ - 1; high++;
398: /* shift up all the later entries in this row */
399: for (ii=N; ii>=i; ii--) {
400: rp[ii+1] = rp[ii];
401: PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));
402: }
403: if (N >= i) {
404: PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));
405: }
406: rp[i] = col;
407: bap = ap + bs2*i;
408: if (roworiented) {
409: for (ii=0; ii<bs; ii++) {
410: for (jj=ii; jj<bs2; jj+=bs) {
411: bap[jj] = *value++;
412: }
413: }
414: } else {
415: for (ii=0; ii<bs; ii++) {
416: for (jj=0; jj<bs; jj++) {
417: *bap++ = *value++;
418: }
419: }
420: }
421: noinsert2:;
422: ailen[row] = nrow;
423: return(0);
424: }
426: /*
427: This routine could be optimized by removing the need for the block copy below and passing stride information
428: to the above inline routines; similarly in MatSetValuesBlocked_MPIBAIJ()
429: */
430: PetscErrorCode MatSetValuesBlocked_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv)
431: {
432: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
433: const MatScalar *value;
434: MatScalar *barray =baij->barray;
435: PetscBool roworiented = baij->roworiented,ignore_ltriangular = ((Mat_SeqSBAIJ*)baij->A->data)->ignore_ltriangular;
436: PetscErrorCode ierr;
437: PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs;
438: PetscInt rend=baij->rendbs,cstart=baij->rstartbs,stepval;
439: PetscInt cend=baij->rendbs,bs=mat->rmap->bs,bs2=baij->bs2;
442: if (!barray) {
443: PetscMalloc1(bs2,&barray);
444: baij->barray = barray;
445: }
447: if (roworiented) {
448: stepval = (n-1)*bs;
449: } else {
450: stepval = (m-1)*bs;
451: }
452: for (i=0; i<m; i++) {
453: if (im[i] < 0) continue;
454: #if defined(PETSC_USE_DEBUG)
455: if (im[i] >= baij->Mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Block indexed row too large %D max %D",im[i],baij->Mbs-1);
456: #endif
457: if (im[i] >= rstart && im[i] < rend) {
458: row = im[i] - rstart;
459: for (j=0; j<n; j++) {
460: if (im[i] > in[j]) {
461: if (ignore_ltriangular) continue; /* ignore lower triangular blocks */
462: else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_USER,"Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)");
463: }
464: /* If NumCol = 1 then a copy is not required */
465: if ((roworiented) && (n == 1)) {
466: barray = (MatScalar*) v + i*bs2;
467: } else if ((!roworiented) && (m == 1)) {
468: barray = (MatScalar*) v + j*bs2;
469: } else { /* Here a copy is required */
470: if (roworiented) {
471: value = v + i*(stepval+bs)*bs + j*bs;
472: } else {
473: value = v + j*(stepval+bs)*bs + i*bs;
474: }
475: for (ii=0; ii<bs; ii++,value+=stepval) {
476: for (jj=0; jj<bs; jj++) {
477: *barray++ = *value++;
478: }
479: }
480: barray -=bs2;
481: }
483: if (in[j] >= cstart && in[j] < cend) {
484: col = in[j] - cstart;
485: MatSetValuesBlocked_SeqSBAIJ_Inlined(baij->A,row,col,barray,addv,im[i],in[j]);
486: } else if (in[j] < 0) continue;
487: #if defined(PETSC_USE_DEBUG)
488: else if (in[j] >= baij->Nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Block indexed column too large %D max %D",in[j],baij->Nbs-1);
489: #endif
490: else {
491: if (mat->was_assembled) {
492: if (!baij->colmap) {
493: MatCreateColmap_MPIBAIJ_Private(mat);
494: }
496: #if defined(PETSC_USE_DEBUG)
497: #if defined(PETSC_USE_CTABLE)
498: { PetscInt data;
499: PetscTableFind(baij->colmap,in[j]+1,&data);
500: if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
501: }
502: #else
503: if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
504: #endif
505: #endif
506: #if defined(PETSC_USE_CTABLE)
507: PetscTableFind(baij->colmap,in[j]+1,&col);
508: col = (col - 1)/bs;
509: #else
510: col = (baij->colmap[in[j]] - 1)/bs;
511: #endif
512: if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
513: MatDisAssemble_MPISBAIJ(mat);
514: col = in[j];
515: }
516: } else col = in[j];
517: MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B,row,col,barray,addv,im[i],in[j]);
518: }
519: }
520: } else {
521: if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process block indexed row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]);
522: if (!baij->donotstash) {
523: if (roworiented) {
524: MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
525: } else {
526: MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
527: }
528: }
529: }
530: }
531: return(0);
532: }
534: PetscErrorCode MatGetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
535: {
536: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
538: PetscInt bs = mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend;
539: PetscInt bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data;
542: for (i=0; i<m; i++) {
543: if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]); */
544: 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);
545: if (idxm[i] >= bsrstart && idxm[i] < bsrend) {
546: row = idxm[i] - bsrstart;
547: for (j=0; j<n; j++) {
548: if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column %D",idxn[j]); */
549: 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);
550: if (idxn[j] >= bscstart && idxn[j] < bscend) {
551: col = idxn[j] - bscstart;
552: MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);
553: } else {
554: if (!baij->colmap) {
555: MatCreateColmap_MPIBAIJ_Private(mat);
556: }
557: #if defined(PETSC_USE_CTABLE)
558: PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);
559: data--;
560: #else
561: data = baij->colmap[idxn[j]/bs]-1;
562: #endif
563: if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0;
564: else {
565: col = data + idxn[j]%bs;
566: MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);
567: }
568: }
569: }
570: } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
571: }
572: return(0);
573: }
575: PetscErrorCode MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm)
576: {
577: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
579: PetscReal sum[2],*lnorm2;
582: if (baij->size == 1) {
583: MatNorm(baij->A,type,norm);
584: } else {
585: if (type == NORM_FROBENIUS) {
586: PetscMalloc1(2,&lnorm2);
587: MatNorm(baij->A,type,lnorm2);
588: *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++; /* squar power of norm(A) */
589: MatNorm(baij->B,type,lnorm2);
590: *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--; /* squar power of norm(B) */
591: MPIU_Allreduce(lnorm2,sum,2,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
592: *norm = PetscSqrtReal(sum[0] + 2*sum[1]);
593: PetscFree(lnorm2);
594: } else if (type == NORM_INFINITY || type == NORM_1) { /* max row/column sum */
595: Mat_SeqSBAIJ *amat=(Mat_SeqSBAIJ*)baij->A->data;
596: Mat_SeqBAIJ *bmat=(Mat_SeqBAIJ*)baij->B->data;
597: PetscReal *rsum,*rsum2,vabs;
598: PetscInt *jj,*garray=baij->garray,rstart=baij->rstartbs,nz;
599: PetscInt brow,bcol,col,bs=baij->A->rmap->bs,row,grow,gcol,mbs=amat->mbs;
600: MatScalar *v;
602: PetscMalloc2(mat->cmap->N,&rsum,mat->cmap->N,&rsum2);
603: PetscMemzero(rsum,mat->cmap->N*sizeof(PetscReal));
604: /* Amat */
605: v = amat->a; jj = amat->j;
606: for (brow=0; brow<mbs; brow++) {
607: grow = bs*(rstart + brow);
608: nz = amat->i[brow+1] - amat->i[brow];
609: for (bcol=0; bcol<nz; bcol++) {
610: gcol = bs*(rstart + *jj); jj++;
611: for (col=0; col<bs; col++) {
612: for (row=0; row<bs; row++) {
613: vabs = PetscAbsScalar(*v); v++;
614: rsum[gcol+col] += vabs;
615: /* non-diagonal block */
616: if (bcol > 0 && vabs > 0.0) rsum[grow+row] += vabs;
617: }
618: }
619: }
620: PetscLogFlops(nz*bs*bs);
621: }
622: /* Bmat */
623: v = bmat->a; jj = bmat->j;
624: for (brow=0; brow<mbs; brow++) {
625: grow = bs*(rstart + brow);
626: nz = bmat->i[brow+1] - bmat->i[brow];
627: for (bcol=0; bcol<nz; bcol++) {
628: gcol = bs*garray[*jj]; jj++;
629: for (col=0; col<bs; col++) {
630: for (row=0; row<bs; row++) {
631: vabs = PetscAbsScalar(*v); v++;
632: rsum[gcol+col] += vabs;
633: rsum[grow+row] += vabs;
634: }
635: }
636: }
637: PetscLogFlops(nz*bs*bs);
638: }
639: MPIU_Allreduce(rsum,rsum2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
640: *norm = 0.0;
641: for (col=0; col<mat->cmap->N; col++) {
642: if (rsum2[col] > *norm) *norm = rsum2[col];
643: }
644: PetscFree2(rsum,rsum2);
645: } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for this norm yet");
646: }
647: return(0);
648: }
650: PetscErrorCode MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode)
651: {
652: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
654: PetscInt nstash,reallocs;
657: if (baij->donotstash || mat->nooffprocentries) return(0);
659: MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
660: MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);
661: MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
662: PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);
663: MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
664: PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
665: return(0);
666: }
668: PetscErrorCode MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode)
669: {
670: Mat_MPISBAIJ *baij=(Mat_MPISBAIJ*)mat->data;
671: Mat_SeqSBAIJ *a =(Mat_SeqSBAIJ*)baij->A->data;
673: PetscInt i,j,rstart,ncols,flg,bs2=baij->bs2;
674: PetscInt *row,*col;
675: PetscBool other_disassembled;
676: PetscMPIInt n;
677: PetscBool r1,r2,r3;
678: MatScalar *val;
680: /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */
682: if (!baij->donotstash && !mat->nooffprocentries) {
683: while (1) {
684: MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);
685: if (!flg) break;
687: for (i=0; i<n;) {
688: /* Now identify the consecutive vals belonging to the same row */
689: for (j=i,rstart=row[j]; j<n; j++) {
690: if (row[j] != rstart) break;
691: }
692: if (j < n) ncols = j-i;
693: else ncols = n-i;
694: /* Now assemble all these values with a single function call */
695: MatSetValues_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);
696: i = j;
697: }
698: }
699: MatStashScatterEnd_Private(&mat->stash);
700: /* Now process the block-stash. Since the values are stashed column-oriented,
701: set the roworiented flag to column oriented, and after MatSetValues()
702: restore the original flags */
703: r1 = baij->roworiented;
704: r2 = a->roworiented;
705: r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented;
707: baij->roworiented = PETSC_FALSE;
708: a->roworiented = PETSC_FALSE;
710: ((Mat_SeqBAIJ*)baij->B->data)->roworiented = PETSC_FALSE; /* b->roworinted */
711: while (1) {
712: MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);
713: if (!flg) break;
715: for (i=0; i<n;) {
716: /* Now identify the consecutive vals belonging to the same row */
717: for (j=i,rstart=row[j]; j<n; j++) {
718: if (row[j] != rstart) break;
719: }
720: if (j < n) ncols = j-i;
721: else ncols = n-i;
722: MatSetValuesBlocked_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,mat->insertmode);
723: i = j;
724: }
725: }
726: MatStashScatterEnd_Private(&mat->bstash);
728: baij->roworiented = r1;
729: a->roworiented = r2;
731: ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworinted */
732: }
734: MatAssemblyBegin(baij->A,mode);
735: MatAssemblyEnd(baij->A,mode);
737: /* determine if any processor has disassembled, if so we must
738: also disassemble ourselfs, in order that we may reassemble. */
739: /*
740: if nonzero structure of submatrix B cannot change then we know that
741: no processor disassembled thus we can skip this stuff
742: */
743: if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) {
744: MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
745: if (mat->was_assembled && !other_disassembled) {
746: MatDisAssemble_MPISBAIJ(mat);
747: }
748: }
750: if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
751: MatSetUpMultiply_MPISBAIJ(mat); /* setup Mvctx and sMvctx */
752: }
753: MatAssemblyBegin(baij->B,mode);
754: MatAssemblyEnd(baij->B,mode);
756: PetscFree2(baij->rowvalues,baij->rowindices);
758: baij->rowvalues = 0;
760: /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
761: if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
762: PetscObjectState state = baij->A->nonzerostate + baij->B->nonzerostate;
763: MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));
764: }
765: return(0);
766: }
768: extern PetscErrorCode MatSetValues_MPIBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
769: #include <petscdraw.h>
770: static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
771: {
772: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
773: PetscErrorCode ierr;
774: PetscInt bs = mat->rmap->bs;
775: PetscMPIInt rank = baij->rank;
776: PetscBool iascii,isdraw;
777: PetscViewer sviewer;
778: PetscViewerFormat format;
781: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
782: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
783: if (iascii) {
784: PetscViewerGetFormat(viewer,&format);
785: if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
786: MatInfo info;
787: MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
788: MatGetInfo(mat,MAT_LOCAL,&info);
789: PetscViewerASCIIPushSynchronized(viewer);
790: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %g\n",rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(double)info.memory);
791: MatGetInfo(baij->A,MAT_LOCAL,&info);
792: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
793: MatGetInfo(baij->B,MAT_LOCAL,&info);
794: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
795: PetscViewerFlush(viewer);
796: PetscViewerASCIIPopSynchronized(viewer);
797: PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
798: VecScatterView(baij->Mvctx,viewer);
799: return(0);
800: } else if (format == PETSC_VIEWER_ASCII_INFO) {
801: PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);
802: return(0);
803: } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
804: return(0);
805: }
806: }
808: if (isdraw) {
809: PetscDraw draw;
810: PetscBool isnull;
811: PetscViewerDrawGetDraw(viewer,0,&draw);
812: PetscDrawIsNull(draw,&isnull);
813: if (isnull) return(0);
814: }
816: {
817: /* assemble the entire matrix onto first processor. */
818: Mat A;
819: Mat_SeqSBAIJ *Aloc;
820: Mat_SeqBAIJ *Bloc;
821: PetscInt M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs;
822: MatScalar *a;
823: const char *matname;
825: /* Should this be the same type as mat? */
826: MatCreate(PetscObjectComm((PetscObject)mat),&A);
827: if (!rank) {
828: MatSetSizes(A,M,N,M,N);
829: } else {
830: MatSetSizes(A,0,0,M,N);
831: }
832: MatSetType(A,MATMPISBAIJ);
833: MatMPISBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);
834: MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);
835: PetscLogObjectParent((PetscObject)mat,(PetscObject)A);
837: /* copy over the A part */
838: Aloc = (Mat_SeqSBAIJ*)baij->A->data;
839: ai = Aloc->i; aj = Aloc->j; a = Aloc->a;
840: PetscMalloc1(bs,&rvals);
842: for (i=0; i<mbs; i++) {
843: rvals[0] = bs*(baij->rstartbs + i);
844: for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
845: for (j=ai[i]; j<ai[i+1]; j++) {
846: col = (baij->cstartbs+aj[j])*bs;
847: for (k=0; k<bs; k++) {
848: MatSetValues_MPISBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
849: col++;
850: a += bs;
851: }
852: }
853: }
854: /* copy over the B part */
855: Bloc = (Mat_SeqBAIJ*)baij->B->data;
856: ai = Bloc->i; aj = Bloc->j; a = Bloc->a;
857: for (i=0; i<mbs; i++) {
859: rvals[0] = bs*(baij->rstartbs + i);
860: for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
861: for (j=ai[i]; j<ai[i+1]; j++) {
862: col = baij->garray[aj[j]]*bs;
863: for (k=0; k<bs; k++) {
864: MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
865: col++;
866: a += bs;
867: }
868: }
869: }
870: PetscFree(rvals);
871: MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
872: MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
873: /*
874: Everyone has to call to draw the matrix since the graphics waits are
875: synchronized across all processors that share the PetscDraw object
876: */
877: PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
878: PetscObjectGetName((PetscObject)mat,&matname);
879: if (!rank) {
880: PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,matname);
881: MatView_SeqSBAIJ(((Mat_MPISBAIJ*)(A->data))->A,sviewer);
882: }
883: PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
884: PetscViewerFlush(viewer);
885: MatDestroy(&A);
886: }
887: return(0);
888: }
890: static PetscErrorCode MatView_MPISBAIJ_Binary(Mat mat,PetscViewer viewer)
891: {
892: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)mat->data;
893: Mat_SeqSBAIJ *A = (Mat_SeqSBAIJ*)a->A->data;
894: Mat_SeqBAIJ *B = (Mat_SeqBAIJ*)a->B->data;
896: PetscInt i,*row_lens,*crow_lens,bs = mat->rmap->bs,j,k,bs2=a->bs2,header[4],nz,rlen;
897: PetscInt *range=0,nzmax,*column_indices,cnt,col,*garray = a->garray,cstart = mat->cmap->rstart/bs,len,pcnt,l,ll;
898: int fd;
899: PetscScalar *column_values;
900: FILE *file;
901: PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag;
902: PetscInt message_count,flowcontrolcount;
905: MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
906: MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);
907: nz = bs2*(A->nz + B->nz);
908: rlen = mat->rmap->n;
909: PetscViewerBinaryGetDescriptor(viewer,&fd);
910: if (!rank) {
911: header[0] = MAT_FILE_CLASSID;
912: header[1] = mat->rmap->N;
913: header[2] = mat->cmap->N;
915: MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
916: PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);
917: /* get largest number of rows any processor has */
918: range = mat->rmap->range;
919: for (i=1; i<size; i++) {
920: rlen = PetscMax(rlen,range[i+1] - range[i]);
921: }
922: } else {
923: MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));
924: }
926: PetscMalloc1(rlen/bs,&crow_lens);
927: /* compute lengths of each row */
928: for (i=0; i<a->mbs; i++) {
929: crow_lens[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i];
930: }
931: /* store the row lengths to the file */
932: PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
933: if (!rank) {
934: MPI_Status status;
935: PetscMalloc1(rlen,&row_lens);
936: rlen = (range[1] - range[0])/bs;
937: for (i=0; i<rlen; i++) {
938: for (j=0; j<bs; j++) {
939: row_lens[i*bs+j] = bs*crow_lens[i];
940: }
941: }
942: PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);
943: for (i=1; i<size; i++) {
944: rlen = (range[i+1] - range[i])/bs;
945: PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
946: MPI_Recv(crow_lens,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
947: for (k=0; k<rlen; k++) {
948: for (j=0; j<bs; j++) {
949: row_lens[k*bs+j] = bs*crow_lens[k];
950: }
951: }
952: PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);
953: }
954: PetscViewerFlowControlEndMaster(viewer,&message_count);
955: PetscFree(row_lens);
956: } else {
957: PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
958: MPI_Send(crow_lens,mat->rmap->n/bs,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
959: PetscViewerFlowControlEndWorker(viewer,&message_count);
960: }
961: PetscFree(crow_lens);
963: /* load up the local column indices. Include for all rows not just one for each block row since process 0 does not have the
964: information needed to make it for each row from a block row. This does require more communication but still not more than
965: the communication needed for the nonzero values */
966: nzmax = nz; /* space a largest processor needs */
967: MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));
968: PetscMalloc1(nzmax,&column_indices);
969: cnt = 0;
970: for (i=0; i<a->mbs; i++) {
971: pcnt = cnt;
972: for (j=B->i[i]; j<B->i[i+1]; j++) {
973: if ((col = garray[B->j[j]]) > cstart) break;
974: for (l=0; l<bs; l++) {
975: column_indices[cnt++] = bs*col+l;
976: }
977: }
978: for (k=A->i[i]; k<A->i[i+1]; k++) {
979: for (l=0; l<bs; l++) {
980: column_indices[cnt++] = bs*(A->j[k] + cstart)+l;
981: }
982: }
983: for (; j<B->i[i+1]; j++) {
984: for (l=0; l<bs; l++) {
985: column_indices[cnt++] = bs*garray[B->j[j]]+l;
986: }
987: }
988: len = cnt - pcnt;
989: for (k=1; k<bs; k++) {
990: PetscMemcpy(&column_indices[cnt],&column_indices[pcnt],len*sizeof(PetscInt));
991: cnt += len;
992: }
993: }
994: if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz);
996: /* store the columns to the file */
997: PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
998: if (!rank) {
999: MPI_Status status;
1000: PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);
1001: for (i=1; i<size; i++) {
1002: PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1003: MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1004: MPI_Recv(column_indices,cnt,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1005: PetscBinaryWrite(fd,column_indices,cnt,PETSC_INT,PETSC_TRUE);
1006: }
1007: PetscViewerFlowControlEndMaster(viewer,&message_count);
1008: } else {
1009: PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1010: MPI_Send(&cnt,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1011: MPI_Send(column_indices,cnt,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1012: PetscViewerFlowControlEndWorker(viewer,&message_count);
1013: }
1014: PetscFree(column_indices);
1016: /* load up the numerical values */
1017: PetscMalloc1(nzmax,&column_values);
1018: cnt = 0;
1019: for (i=0; i<a->mbs; i++) {
1020: rlen = bs*(B->i[i+1] - B->i[i] + A->i[i+1] - A->i[i]);
1021: for (j=B->i[i]; j<B->i[i+1]; j++) {
1022: if (garray[B->j[j]] > cstart) break;
1023: for (l=0; l<bs; l++) {
1024: for (ll=0; ll<bs; ll++) {
1025: column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll];
1026: }
1027: }
1028: cnt += bs;
1029: }
1030: for (k=A->i[i]; k<A->i[i+1]; k++) {
1031: for (l=0; l<bs; l++) {
1032: for (ll=0; ll<bs; ll++) {
1033: column_values[cnt + l*rlen + ll] = A->a[bs2*k+l+bs*ll];
1034: }
1035: }
1036: cnt += bs;
1037: }
1038: for (; j<B->i[i+1]; j++) {
1039: for (l=0; l<bs; l++) {
1040: for (ll=0; ll<bs; ll++) {
1041: column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll];
1042: }
1043: }
1044: cnt += bs;
1045: }
1046: cnt += (bs-1)*rlen;
1047: }
1048: if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz);
1050: /* store the column values to the file */
1051: PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);
1052: if (!rank) {
1053: MPI_Status status;
1054: PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);
1055: for (i=1; i<size; i++) {
1056: PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);
1057: MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);
1058: MPI_Recv(column_values,cnt,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat),&status);
1059: PetscBinaryWrite(fd,column_values,cnt,PETSC_SCALAR,PETSC_TRUE);
1060: }
1061: PetscViewerFlowControlEndMaster(viewer,&message_count);
1062: } else {
1063: PetscViewerFlowControlStepWorker(viewer,rank,&message_count);
1064: MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));
1065: MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));
1066: PetscViewerFlowControlEndWorker(viewer,&message_count);
1067: }
1068: PetscFree(column_values);
1070: PetscViewerBinaryGetInfoPointer(viewer,&file);
1071: if (file) {
1072: fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs);
1073: }
1074: return(0);
1075: }
1077: PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer)
1078: {
1080: PetscBool iascii,isdraw,issocket,isbinary;
1083: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1084: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1085: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
1086: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1087: if (iascii || isdraw || issocket) {
1088: MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);
1089: } else if (isbinary) {
1090: MatView_MPISBAIJ_Binary(mat,viewer);
1091: }
1092: return(0);
1093: }
1095: PetscErrorCode MatDestroy_MPISBAIJ(Mat mat)
1096: {
1097: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
1101: #if defined(PETSC_USE_LOG)
1102: PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N);
1103: #endif
1104: MatStashDestroy_Private(&mat->stash);
1105: MatStashDestroy_Private(&mat->bstash);
1106: MatDestroy(&baij->A);
1107: MatDestroy(&baij->B);
1108: #if defined(PETSC_USE_CTABLE)
1109: PetscTableDestroy(&baij->colmap);
1110: #else
1111: PetscFree(baij->colmap);
1112: #endif
1113: PetscFree(baij->garray);
1114: VecDestroy(&baij->lvec);
1115: VecScatterDestroy(&baij->Mvctx);
1116: VecDestroy(&baij->slvec0);
1117: VecDestroy(&baij->slvec0b);
1118: VecDestroy(&baij->slvec1);
1119: VecDestroy(&baij->slvec1a);
1120: VecDestroy(&baij->slvec1b);
1121: VecScatterDestroy(&baij->sMvctx);
1122: PetscFree2(baij->rowvalues,baij->rowindices);
1123: PetscFree(baij->barray);
1124: PetscFree(baij->hd);
1125: VecDestroy(&baij->diag);
1126: VecDestroy(&baij->bb1);
1127: VecDestroy(&baij->xx1);
1128: #if defined(PETSC_USE_REAL_MAT_SINGLE)
1129: PetscFree(baij->setvaluescopy);
1130: #endif
1131: PetscFree(baij->in_loc);
1132: PetscFree(baij->v_loc);
1133: PetscFree(baij->rangebs);
1134: PetscFree(mat->data);
1136: PetscObjectChangeTypeName((PetscObject)mat,0);
1137: PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
1138: PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
1139: PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C",NULL);
1140: PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_mpisbstrm_C",NULL);
1141: #if defined(PETSC_HAVE_ELEMENTAL)
1142: PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_elemental_C",NULL);
1143: #endif
1144: return(0);
1145: }
1147: PetscErrorCode MatMult_MPISBAIJ_Hermitian(Mat A,Vec xx,Vec yy)
1148: {
1149: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1150: PetscErrorCode ierr;
1151: PetscInt nt,mbs=a->mbs,bs=A->rmap->bs;
1152: PetscScalar *from;
1153: const PetscScalar *x;
1156: VecGetLocalSize(xx,&nt);
1157: if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");
1159: /* diagonal part */
1160: (*a->A->ops->mult)(a->A,xx,a->slvec1a);
1161: VecSet(a->slvec1b,0.0);
1163: /* subdiagonal part */
1164: (*a->B->ops->multhermitiantranspose)(a->B,xx,a->slvec0b);
1166: /* copy x into the vec slvec0 */
1167: VecGetArray(a->slvec0,&from);
1168: VecGetArrayRead(xx,&x);
1170: PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
1171: VecRestoreArray(a->slvec0,&from);
1172: VecRestoreArrayRead(xx,&x);
1174: VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1175: VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1176: /* supperdiagonal part */
1177: (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);
1178: return(0);
1179: }
1181: PetscErrorCode MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy)
1182: {
1183: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1184: PetscErrorCode ierr;
1185: PetscInt nt,mbs=a->mbs,bs=A->rmap->bs;
1186: PetscScalar *from;
1187: const PetscScalar *x;
1190: VecGetLocalSize(xx,&nt);
1191: if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");
1193: /* diagonal part */
1194: (*a->A->ops->mult)(a->A,xx,a->slvec1a);
1195: VecSet(a->slvec1b,0.0);
1197: /* subdiagonal part */
1198: (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);
1200: /* copy x into the vec slvec0 */
1201: VecGetArray(a->slvec0,&from);
1202: VecGetArrayRead(xx,&x);
1204: PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
1205: VecRestoreArray(a->slvec0,&from);
1206: VecRestoreArrayRead(xx,&x);
1208: VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1209: VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1210: /* supperdiagonal part */
1211: (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);
1212: return(0);
1213: }
1215: PetscErrorCode MatMult_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy)
1216: {
1217: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1219: PetscInt nt;
1222: VecGetLocalSize(xx,&nt);
1223: if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");
1225: VecGetLocalSize(yy,&nt);
1226: if (nt != A->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy");
1228: VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1229: /* do diagonal part */
1230: (*a->A->ops->mult)(a->A,xx,yy);
1231: /* do supperdiagonal part */
1232: VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1233: (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
1234: /* do subdiagonal part */
1235: (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1236: VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1237: VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
1238: return(0);
1239: }
1241: PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1242: {
1243: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1244: PetscErrorCode ierr;
1245: PetscInt mbs=a->mbs,bs=A->rmap->bs;
1246: PetscScalar *from,zero=0.0;
1247: const PetscScalar *x;
1250: /*
1251: PetscSynchronizedPrintf(PetscObjectComm((PetscObject)A)," MatMultAdd is called ...\n");
1252: PetscSynchronizedFlush(PetscObjectComm((PetscObject)A),PETSC_STDOUT);
1253: */
1254: /* diagonal part */
1255: (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);
1256: VecSet(a->slvec1b,zero);
1258: /* subdiagonal part */
1259: (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);
1261: /* copy x into the vec slvec0 */
1262: VecGetArray(a->slvec0,&from);
1263: VecGetArrayRead(xx,&x);
1264: PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
1265: VecRestoreArray(a->slvec0,&from);
1267: VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1268: VecRestoreArrayRead(xx,&x);
1269: VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1271: /* supperdiagonal part */
1272: (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);
1273: return(0);
1274: }
1276: PetscErrorCode MatMultAdd_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy,Vec zz)
1277: {
1278: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1282: VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1283: /* do diagonal part */
1284: (*a->A->ops->multadd)(a->A,xx,yy,zz);
1285: /* do supperdiagonal part */
1286: VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
1287: (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);
1289: /* do subdiagonal part */
1290: (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
1291: VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1292: VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
1293: return(0);
1294: }
1296: /*
1297: This only works correctly for square matrices where the subblock A->A is the
1298: diagonal block
1299: */
1300: PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v)
1301: {
1302: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1306: /* if (a->rmap->N != a->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */
1307: MatGetDiagonal(a->A,v);
1308: return(0);
1309: }
1311: PetscErrorCode MatScale_MPISBAIJ(Mat A,PetscScalar aa)
1312: {
1313: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1317: MatScale(a->A,aa);
1318: MatScale(a->B,aa);
1319: return(0);
1320: }
1322: PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1323: {
1324: Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data;
1325: PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p;
1327: PetscInt bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB;
1328: PetscInt nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend;
1329: PetscInt *cmap,*idx_p,cstart = mat->rstartbs;
1332: if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active");
1333: mat->getrowactive = PETSC_TRUE;
1335: if (!mat->rowvalues && (idx || v)) {
1336: /*
1337: allocate enough space to hold information from the longest row.
1338: */
1339: Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data;
1340: Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ*)mat->B->data;
1341: PetscInt max = 1,mbs = mat->mbs,tmp;
1342: for (i=0; i<mbs; i++) {
1343: tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */
1344: if (max < tmp) max = tmp;
1345: }
1346: PetscMalloc2(max*bs2,&mat->rowvalues,max*bs2,&mat->rowindices);
1347: }
1349: if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows");
1350: lrow = row - brstart; /* local row index */
1352: pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
1353: if (!v) {pvA = 0; pvB = 0;}
1354: if (!idx) {pcA = 0; if (!v) pcB = 0;}
1355: (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
1356: (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
1357: nztot = nzA + nzB;
1359: cmap = mat->garray;
1360: if (v || idx) {
1361: if (nztot) {
1362: /* Sort by increasing column numbers, assuming A and B already sorted */
1363: PetscInt imark = -1;
1364: if (v) {
1365: *v = v_p = mat->rowvalues;
1366: for (i=0; i<nzB; i++) {
1367: if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i];
1368: else break;
1369: }
1370: imark = i;
1371: for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i];
1372: for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i];
1373: }
1374: if (idx) {
1375: *idx = idx_p = mat->rowindices;
1376: if (imark > -1) {
1377: for (i=0; i<imark; i++) {
1378: idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1379: }
1380: } else {
1381: for (i=0; i<nzB; i++) {
1382: if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1383: else break;
1384: }
1385: imark = i;
1386: }
1387: for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i];
1388: for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ;
1389: }
1390: } else {
1391: if (idx) *idx = 0;
1392: if (v) *v = 0;
1393: }
1394: }
1395: *nz = nztot;
1396: (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
1397: (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
1398: return(0);
1399: }
1401: PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1402: {
1403: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
1406: if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first");
1407: baij->getrowactive = PETSC_FALSE;
1408: return(0);
1409: }
1411: PetscErrorCode MatGetRowUpperTriangular_MPISBAIJ(Mat A)
1412: {
1413: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1414: Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;
1417: aA->getrow_utriangular = PETSC_TRUE;
1418: return(0);
1419: }
1420: PetscErrorCode MatRestoreRowUpperTriangular_MPISBAIJ(Mat A)
1421: {
1422: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1423: Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;
1426: aA->getrow_utriangular = PETSC_FALSE;
1427: return(0);
1428: }
1430: PetscErrorCode MatRealPart_MPISBAIJ(Mat A)
1431: {
1432: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1436: MatRealPart(a->A);
1437: MatRealPart(a->B);
1438: return(0);
1439: }
1441: PetscErrorCode MatImaginaryPart_MPISBAIJ(Mat A)
1442: {
1443: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1447: MatImaginaryPart(a->A);
1448: MatImaginaryPart(a->B);
1449: return(0);
1450: }
1452: /* Check if isrow is a subset of iscol_local, called by MatCreateSubMatrix_MPISBAIJ()
1453: Input: isrow - distributed(parallel),
1454: iscol_local - locally owned (seq)
1455: */
1456: PetscErrorCode ISEqual_private(IS isrow,IS iscol_local,PetscBool *flg)
1457: {
1459: PetscInt sz1,sz2,*a1,*a2,i,j,k,nmatch;
1460: const PetscInt *ptr1,*ptr2;
1463: ISGetLocalSize(isrow,&sz1);
1464: ISGetLocalSize(iscol_local,&sz2);
1465: if (sz1 > sz2) {
1466: *flg = PETSC_FALSE;
1467: return(0);
1468: }
1470: ISGetIndices(isrow,&ptr1);
1471: ISGetIndices(iscol_local,&ptr2);
1473: PetscMalloc1(sz1,&a1);
1474: PetscMalloc1(sz2,&a2);
1475: PetscMemcpy(a1,ptr1,sz1*sizeof(PetscInt));
1476: PetscMemcpy(a2,ptr2,sz2*sizeof(PetscInt));
1477: PetscSortInt(sz1,a1);
1478: PetscSortInt(sz2,a2);
1480: nmatch=0;
1481: k = 0;
1482: for (i=0; i<sz1; i++){
1483: for (j=k; j<sz2; j++){
1484: if (a1[i] == a2[j]) {
1485: k = j; nmatch++;
1486: break;
1487: }
1488: }
1489: }
1490: ISRestoreIndices(isrow,&ptr1);
1491: ISRestoreIndices(iscol_local,&ptr2);
1492: PetscFree(a1);
1493: PetscFree(a2);
1494: if (nmatch < sz1) {
1495: *flg = PETSC_FALSE;
1496: } else {
1497: *flg = PETSC_TRUE;
1498: }
1499: return(0);
1500: }
1502: PetscErrorCode MatCreateSubMatrix_MPISBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
1503: {
1505: IS iscol_local;
1506: PetscInt csize;
1507: PetscBool isequal;
1510: ISGetLocalSize(iscol,&csize);
1511: if (call == MAT_REUSE_MATRIX) {
1512: PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);
1513: if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
1514: } else {
1515: ISAllGather(iscol,&iscol_local);
1516: ISEqual_private(isrow,iscol_local,&isequal);
1517: if (!isequal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"For symmetric format, iscol must equal isrow");
1518: }
1520: /* now call MatCreateSubMatrix_MPIBAIJ() */
1521: MatCreateSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);
1522: if (call == MAT_INITIAL_MATRIX) {
1523: PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);
1524: ISDestroy(&iscol_local);
1525: }
1526: return(0);
1527: }
1529: PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A)
1530: {
1531: Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data;
1535: MatZeroEntries(l->A);
1536: MatZeroEntries(l->B);
1537: return(0);
1538: }
1540: PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info)
1541: {
1542: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)matin->data;
1543: Mat A = a->A,B = a->B;
1545: PetscReal isend[5],irecv[5];
1548: info->block_size = (PetscReal)matin->rmap->bs;
1550: MatGetInfo(A,MAT_LOCAL,info);
1552: isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
1553: isend[3] = info->memory; isend[4] = info->mallocs;
1555: MatGetInfo(B,MAT_LOCAL,info);
1557: isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
1558: isend[3] += info->memory; isend[4] += info->mallocs;
1559: if (flag == MAT_LOCAL) {
1560: info->nz_used = isend[0];
1561: info->nz_allocated = isend[1];
1562: info->nz_unneeded = isend[2];
1563: info->memory = isend[3];
1564: info->mallocs = isend[4];
1565: } else if (flag == MAT_GLOBAL_MAX) {
1566: MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));
1568: info->nz_used = irecv[0];
1569: info->nz_allocated = irecv[1];
1570: info->nz_unneeded = irecv[2];
1571: info->memory = irecv[3];
1572: info->mallocs = irecv[4];
1573: } else if (flag == MAT_GLOBAL_SUM) {
1574: MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));
1576: info->nz_used = irecv[0];
1577: info->nz_allocated = irecv[1];
1578: info->nz_unneeded = irecv[2];
1579: info->memory = irecv[3];
1580: info->mallocs = irecv[4];
1581: } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag);
1582: info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */
1583: info->fill_ratio_needed = 0;
1584: info->factor_mallocs = 0;
1585: return(0);
1586: }
1588: PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op,PetscBool flg)
1589: {
1590: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1591: Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;
1595: switch (op) {
1596: case MAT_NEW_NONZERO_LOCATIONS:
1597: case MAT_NEW_NONZERO_ALLOCATION_ERR:
1598: case MAT_UNUSED_NONZERO_LOCATION_ERR:
1599: case MAT_KEEP_NONZERO_PATTERN:
1600: case MAT_SUBMAT_SINGLEIS:
1601: case MAT_NEW_NONZERO_LOCATION_ERR:
1602: MatCheckPreallocated(A,1);
1603: MatSetOption(a->A,op,flg);
1604: MatSetOption(a->B,op,flg);
1605: break;
1606: case MAT_ROW_ORIENTED:
1607: MatCheckPreallocated(A,1);
1608: a->roworiented = flg;
1610: MatSetOption(a->A,op,flg);
1611: MatSetOption(a->B,op,flg);
1612: break;
1613: case MAT_NEW_DIAGONALS:
1614: PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1615: break;
1616: case MAT_IGNORE_OFF_PROC_ENTRIES:
1617: a->donotstash = flg;
1618: break;
1619: case MAT_USE_HASH_TABLE:
1620: a->ht_flag = flg;
1621: break;
1622: case MAT_HERMITIAN:
1623: MatCheckPreallocated(A,1);
1624: if (!A->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call MatAssemblyEnd() first");
1625: MatSetOption(a->A,op,flg);
1626: #if defined(PETSC_USE_COMPLEX)
1627: A->ops->mult = MatMult_MPISBAIJ_Hermitian;
1628: #endif
1629: break;
1630: case MAT_SPD:
1631: A->spd_set = PETSC_TRUE;
1632: A->spd = flg;
1633: if (flg) {
1634: A->symmetric = PETSC_TRUE;
1635: A->structurally_symmetric = PETSC_TRUE;
1636: A->symmetric_set = PETSC_TRUE;
1637: A->structurally_symmetric_set = PETSC_TRUE;
1638: }
1639: break;
1640: case MAT_SYMMETRIC:
1641: MatCheckPreallocated(A,1);
1642: MatSetOption(a->A,op,flg);
1643: break;
1644: case MAT_STRUCTURALLY_SYMMETRIC:
1645: MatCheckPreallocated(A,1);
1646: MatSetOption(a->A,op,flg);
1647: break;
1648: case MAT_SYMMETRY_ETERNAL:
1649: if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix must be symmetric");
1650: PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1651: break;
1652: case MAT_IGNORE_LOWER_TRIANGULAR:
1653: aA->ignore_ltriangular = flg;
1654: break;
1655: case MAT_ERROR_LOWER_TRIANGULAR:
1656: aA->ignore_ltriangular = flg;
1657: break;
1658: case MAT_GETROW_UPPERTRIANGULAR:
1659: aA->getrow_utriangular = flg;
1660: break;
1661: default:
1662: SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
1663: }
1664: return(0);
1665: }
1667: PetscErrorCode MatTranspose_MPISBAIJ(Mat A,MatReuse reuse,Mat *B)
1668: {
1672: if (reuse == MAT_INITIAL_MATRIX) {
1673: MatDuplicate(A,MAT_COPY_VALUES,B);
1674: } else if (reuse == MAT_REUSE_MATRIX) {
1675: MatCopy(A,*B,SAME_NONZERO_PATTERN);
1676: }
1677: return(0);
1678: }
1680: PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr)
1681: {
1682: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
1683: Mat a = baij->A, b=baij->B;
1685: PetscInt nv,m,n;
1686: PetscBool flg;
1689: if (ll != rr) {
1690: VecEqual(ll,rr,&flg);
1691: if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n");
1692: }
1693: if (!ll) return(0);
1695: MatGetLocalSize(mat,&m,&n);
1696: if (m != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"For symmetric format, local size %d %d must be same",m,n);
1698: VecGetLocalSize(rr,&nv);
1699: if (nv!=n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left and right vector non-conforming local size");
1701: VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);
1703: /* left diagonalscale the off-diagonal part */
1704: (*b->ops->diagonalscale)(b,ll,NULL);
1706: /* scale the diagonal part */
1707: (*a->ops->diagonalscale)(a,ll,rr);
1709: /* right diagonalscale the off-diagonal part */
1710: VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);
1711: (*b->ops->diagonalscale)(b,NULL,baij->lvec);
1712: return(0);
1713: }
1715: PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A)
1716: {
1717: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1721: MatSetUnfactored(a->A);
1722: return(0);
1723: }
1725: static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat*);
1727: PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscBool *flag)
1728: {
1729: Mat_MPISBAIJ *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data;
1730: Mat a,b,c,d;
1731: PetscBool flg;
1735: a = matA->A; b = matA->B;
1736: c = matB->A; d = matB->B;
1738: MatEqual(a,c,&flg);
1739: if (flg) {
1740: MatEqual(b,d,&flg);
1741: }
1742: MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
1743: return(0);
1744: }
1746: PetscErrorCode MatCopy_MPISBAIJ(Mat A,Mat B,MatStructure str)
1747: {
1749: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1750: Mat_MPISBAIJ *b = (Mat_MPISBAIJ*)B->data;
1753: /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
1754: if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
1755: MatGetRowUpperTriangular(A);
1756: MatCopy_Basic(A,B,str);
1757: MatRestoreRowUpperTriangular(A);
1758: } else {
1759: MatCopy(a->A,b->A,str);
1760: MatCopy(a->B,b->B,str);
1761: }
1762: PetscObjectStateIncrease((PetscObject)B);
1763: return(0);
1764: }
1766: PetscErrorCode MatSetUp_MPISBAIJ(Mat A)
1767: {
1771: MatMPISBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);
1772: return(0);
1773: }
1775: PetscErrorCode MatAXPY_MPISBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
1776: {
1778: Mat_MPISBAIJ *xx=(Mat_MPISBAIJ*)X->data,*yy=(Mat_MPISBAIJ*)Y->data;
1779: PetscBLASInt bnz,one=1;
1780: Mat_SeqSBAIJ *xa,*ya;
1781: Mat_SeqBAIJ *xb,*yb;
1784: if (str == SAME_NONZERO_PATTERN) {
1785: PetscScalar alpha = a;
1786: xa = (Mat_SeqSBAIJ*)xx->A->data;
1787: ya = (Mat_SeqSBAIJ*)yy->A->data;
1788: PetscBLASIntCast(xa->nz,&bnz);
1789: PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xa->a,&one,ya->a,&one));
1790: xb = (Mat_SeqBAIJ*)xx->B->data;
1791: yb = (Mat_SeqBAIJ*)yy->B->data;
1792: PetscBLASIntCast(xb->nz,&bnz);
1793: PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xb->a,&one,yb->a,&one));
1794: PetscObjectStateIncrease((PetscObject)Y);
1795: } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
1796: MatSetOption(X,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
1797: MatAXPY_Basic(Y,a,X,str);
1798: MatSetOption(X,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
1799: } else {
1800: Mat B;
1801: PetscInt *nnz_d,*nnz_o,bs=Y->rmap->bs;
1802: if (bs != X->rmap->bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrices must have same block size");
1803: MatGetRowUpperTriangular(X);
1804: MatGetRowUpperTriangular(Y);
1805: PetscMalloc1(yy->A->rmap->N,&nnz_d);
1806: PetscMalloc1(yy->B->rmap->N,&nnz_o);
1807: MatCreate(PetscObjectComm((PetscObject)Y),&B);
1808: PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
1809: MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
1810: MatSetBlockSizesFromMats(B,Y,Y);
1811: MatSetType(B,MATMPISBAIJ);
1812: MatAXPYGetPreallocation_SeqSBAIJ(yy->A,xx->A,nnz_d);
1813: MatAXPYGetPreallocation_MPIBAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);
1814: MatMPISBAIJSetPreallocation(B,bs,0,nnz_d,0,nnz_o);
1815: MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
1816: MatHeaderReplace(Y,&B);
1817: PetscFree(nnz_d);
1818: PetscFree(nnz_o);
1819: MatRestoreRowUpperTriangular(X);
1820: MatRestoreRowUpperTriangular(Y);
1821: }
1822: return(0);
1823: }
1825: PetscErrorCode MatCreateSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[])
1826: {
1828: PetscInt i;
1829: PetscBool flg;
1832: MatCreateSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B); /* B[] are sbaij matrices */
1833: for (i=0; i<n; i++) {
1834: ISEqual(irow[i],icol[i],&flg);
1835: if (!flg) {
1836: MatSeqSBAIJZeroOps_Private(*B[i]);
1837: }
1838: }
1839: return(0);
1840: }
1842: PetscErrorCode MatShift_MPISBAIJ(Mat Y,PetscScalar a)
1843: {
1845: Mat_MPISBAIJ *maij = (Mat_MPISBAIJ*)Y->data;
1846: Mat_SeqSBAIJ *aij = (Mat_SeqSBAIJ*)maij->A->data;
1849: if (!Y->preallocated) {
1850: MatMPISBAIJSetPreallocation(Y,Y->rmap->bs,1,NULL,0,NULL);
1851: } else if (!aij->nz) {
1852: PetscInt nonew = aij->nonew;
1853: MatSeqSBAIJSetPreallocation(maij->A,Y->rmap->bs,1,NULL);
1854: aij->nonew = nonew;
1855: }
1856: MatShift_Basic(Y,a);
1857: return(0);
1858: }
1860: PetscErrorCode MatMissingDiagonal_MPISBAIJ(Mat A,PetscBool *missing,PetscInt *d)
1861: {
1862: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1866: if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices");
1867: MatMissingDiagonal(a->A,missing,d);
1868: if (d) {
1869: PetscInt rstart;
1870: MatGetOwnershipRange(A,&rstart,NULL);
1871: *d += rstart/A->rmap->bs;
1873: }
1874: return(0);
1875: }
1877: PetscErrorCode MatGetDiagonalBlock_MPISBAIJ(Mat A,Mat *a)
1878: {
1880: *a = ((Mat_MPISBAIJ*)A->data)->A;
1881: return(0);
1882: }
1884: /* -------------------------------------------------------------------*/
1885: static struct _MatOps MatOps_Values = {MatSetValues_MPISBAIJ,
1886: MatGetRow_MPISBAIJ,
1887: MatRestoreRow_MPISBAIJ,
1888: MatMult_MPISBAIJ,
1889: /* 4*/ MatMultAdd_MPISBAIJ,
1890: MatMult_MPISBAIJ, /* transpose versions are same as non-transpose */
1891: MatMultAdd_MPISBAIJ,
1892: 0,
1893: 0,
1894: 0,
1895: /* 10*/ 0,
1896: 0,
1897: 0,
1898: MatSOR_MPISBAIJ,
1899: MatTranspose_MPISBAIJ,
1900: /* 15*/ MatGetInfo_MPISBAIJ,
1901: MatEqual_MPISBAIJ,
1902: MatGetDiagonal_MPISBAIJ,
1903: MatDiagonalScale_MPISBAIJ,
1904: MatNorm_MPISBAIJ,
1905: /* 20*/ MatAssemblyBegin_MPISBAIJ,
1906: MatAssemblyEnd_MPISBAIJ,
1907: MatSetOption_MPISBAIJ,
1908: MatZeroEntries_MPISBAIJ,
1909: /* 24*/ 0,
1910: 0,
1911: 0,
1912: 0,
1913: 0,
1914: /* 29*/ MatSetUp_MPISBAIJ,
1915: 0,
1916: 0,
1917: MatGetDiagonalBlock_MPISBAIJ,
1918: 0,
1919: /* 34*/ MatDuplicate_MPISBAIJ,
1920: 0,
1921: 0,
1922: 0,
1923: 0,
1924: /* 39*/ MatAXPY_MPISBAIJ,
1925: MatCreateSubMatrices_MPISBAIJ,
1926: MatIncreaseOverlap_MPISBAIJ,
1927: MatGetValues_MPISBAIJ,
1928: MatCopy_MPISBAIJ,
1929: /* 44*/ 0,
1930: MatScale_MPISBAIJ,
1931: MatShift_MPISBAIJ,
1932: 0,
1933: 0,
1934: /* 49*/ 0,
1935: 0,
1936: 0,
1937: 0,
1938: 0,
1939: /* 54*/ 0,
1940: 0,
1941: MatSetUnfactored_MPISBAIJ,
1942: 0,
1943: MatSetValuesBlocked_MPISBAIJ,
1944: /* 59*/ MatCreateSubMatrix_MPISBAIJ,
1945: 0,
1946: 0,
1947: 0,
1948: 0,
1949: /* 64*/ 0,
1950: 0,
1951: 0,
1952: 0,
1953: 0,
1954: /* 69*/ MatGetRowMaxAbs_MPISBAIJ,
1955: 0,
1956: 0,
1957: 0,
1958: 0,
1959: /* 74*/ 0,
1960: 0,
1961: 0,
1962: 0,
1963: 0,
1964: /* 79*/ 0,
1965: 0,
1966: 0,
1967: 0,
1968: MatLoad_MPISBAIJ,
1969: /* 84*/ 0,
1970: 0,
1971: 0,
1972: 0,
1973: 0,
1974: /* 89*/ 0,
1975: 0,
1976: 0,
1977: 0,
1978: 0,
1979: /* 94*/ 0,
1980: 0,
1981: 0,
1982: 0,
1983: 0,
1984: /* 99*/ 0,
1985: 0,
1986: 0,
1987: 0,
1988: 0,
1989: /*104*/ 0,
1990: MatRealPart_MPISBAIJ,
1991: MatImaginaryPart_MPISBAIJ,
1992: MatGetRowUpperTriangular_MPISBAIJ,
1993: MatRestoreRowUpperTriangular_MPISBAIJ,
1994: /*109*/ 0,
1995: 0,
1996: 0,
1997: 0,
1998: MatMissingDiagonal_MPISBAIJ,
1999: /*114*/ 0,
2000: 0,
2001: 0,
2002: 0,
2003: 0,
2004: /*119*/ 0,
2005: 0,
2006: 0,
2007: 0,
2008: 0,
2009: /*124*/ 0,
2010: 0,
2011: 0,
2012: 0,
2013: 0,
2014: /*129*/ 0,
2015: 0,
2016: 0,
2017: 0,
2018: 0,
2019: /*134*/ 0,
2020: 0,
2021: 0,
2022: 0,
2023: 0,
2024: /*139*/ MatSetBlockSizes_Default,
2025: 0,
2026: 0,
2027: 0,
2028: 0,
2029: /*144*/MatCreateMPIMatConcatenateSeqMat_MPISBAIJ
2030: };
2032: PetscErrorCode MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz)
2033: {
2034: Mat_MPISBAIJ *b;
2036: PetscInt i,mbs,Mbs;
2039: MatSetBlockSize(B,PetscAbs(bs));
2040: PetscLayoutSetUp(B->rmap);
2041: PetscLayoutSetUp(B->cmap);
2042: PetscLayoutGetBlockSize(B->rmap,&bs);
2044: b = (Mat_MPISBAIJ*)B->data;
2045: mbs = B->rmap->n/bs;
2046: Mbs = B->rmap->N/bs;
2047: if (mbs*bs != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"No of local rows %D must be divisible by blocksize %D",B->rmap->N,bs);
2049: B->rmap->bs = bs;
2050: b->bs2 = bs*bs;
2051: b->mbs = mbs;
2052: b->Mbs = Mbs;
2053: b->nbs = B->cmap->n/bs;
2054: b->Nbs = B->cmap->N/bs;
2056: for (i=0; i<=b->size; i++) {
2057: b->rangebs[i] = B->rmap->range[i]/bs;
2058: }
2059: b->rstartbs = B->rmap->rstart/bs;
2060: b->rendbs = B->rmap->rend/bs;
2062: b->cstartbs = B->cmap->rstart/bs;
2063: b->cendbs = B->cmap->rend/bs;
2065: #if defined(PETSC_USE_CTABLE)
2066: PetscTableDestroy(&b->colmap);
2067: #else
2068: PetscFree(b->colmap);
2069: #endif
2070: PetscFree(b->garray);
2071: VecDestroy(&b->lvec);
2072: VecScatterDestroy(&b->Mvctx);
2073: VecDestroy(&b->slvec0);
2074: VecDestroy(&b->slvec0b);
2075: VecDestroy(&b->slvec1);
2076: VecDestroy(&b->slvec1a);
2077: VecDestroy(&b->slvec1b);
2078: VecScatterDestroy(&b->sMvctx);
2080: /* Because the B will have been resized we simply destroy it and create a new one each time */
2081: MatDestroy(&b->B);
2082: MatCreate(PETSC_COMM_SELF,&b->B);
2083: MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);
2084: MatSetType(b->B,MATSEQBAIJ);
2085: PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);
2087: if (!B->preallocated) {
2088: MatCreate(PETSC_COMM_SELF,&b->A);
2089: MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
2090: MatSetType(b->A,MATSEQSBAIJ);
2091: PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);
2092: MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);
2093: }
2095: MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);
2096: MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);
2098: B->preallocated = PETSC_TRUE;
2099: B->was_assembled = PETSC_FALSE;
2100: B->assembled = PETSC_FALSE;
2101: return(0);
2102: }
2104: PetscErrorCode MatMPISBAIJSetPreallocationCSR_MPISBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[])
2105: {
2106: PetscInt m,rstart,cstart,cend;
2107: PetscInt i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0;
2108: const PetscInt *JJ =0;
2109: PetscScalar *values=0;
2113: if (bs < 1) SETERRQ1(PetscObjectComm((PetscObject)B),PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs);
2114: PetscLayoutSetBlockSize(B->rmap,bs);
2115: PetscLayoutSetBlockSize(B->cmap,bs);
2116: PetscLayoutSetUp(B->rmap);
2117: PetscLayoutSetUp(B->cmap);
2118: PetscLayoutGetBlockSize(B->rmap,&bs);
2119: m = B->rmap->n/bs;
2120: rstart = B->rmap->rstart/bs;
2121: cstart = B->cmap->rstart/bs;
2122: cend = B->cmap->rend/bs;
2124: if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]);
2125: PetscMalloc2(m,&d_nnz,m,&o_nnz);
2126: for (i=0; i<m; i++) {
2127: nz = ii[i+1] - ii[i];
2128: if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz);
2129: nz_max = PetscMax(nz_max,nz);
2130: JJ = jj + ii[i];
2131: for (j=0; j<nz; j++) {
2132: if (*JJ >= cstart) break;
2133: JJ++;
2134: }
2135: d = 0;
2136: for (; j<nz; j++) {
2137: if (*JJ++ >= cend) break;
2138: d++;
2139: }
2140: d_nnz[i] = d;
2141: o_nnz[i] = nz - d;
2142: }
2143: MatMPISBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);
2144: PetscFree2(d_nnz,o_nnz);
2146: values = (PetscScalar*)V;
2147: if (!values) {
2148: PetscMalloc1(bs*bs*nz_max,&values);
2149: PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));
2150: }
2151: for (i=0; i<m; i++) {
2152: PetscInt row = i + rstart;
2153: PetscInt ncols = ii[i+1] - ii[i];
2154: const PetscInt *icols = jj + ii[i];
2155: const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0);
2156: MatSetValuesBlocked_MPISBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);
2157: }
2159: if (!V) { PetscFree(values); }
2160: MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
2161: MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
2162: MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
2163: return(0);
2164: }
2166: /*MC
2167: MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices,
2168: based on block compressed sparse row format. Only the upper triangular portion of the "diagonal" portion of
2169: the matrix is stored.
2171: For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you
2172: can call MatSetOption(Mat, MAT_HERMITIAN);
2174: Options Database Keys:
2175: . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions()
2177: Level: beginner
2179: .seealso: MatCreateMPISBAIJ
2180: M*/
2182: PETSC_INTERN PetscErrorCode MatConvert_MPISBAIJ_MPISBSTRM(Mat,MatType,MatReuse,Mat*);
2184: PETSC_EXTERN PetscErrorCode MatCreate_MPISBAIJ(Mat B)
2185: {
2186: Mat_MPISBAIJ *b;
2188: PetscBool flg = PETSC_FALSE;
2191: PetscNewLog(B,&b);
2192: B->data = (void*)b;
2193: PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
2195: B->ops->destroy = MatDestroy_MPISBAIJ;
2196: B->ops->view = MatView_MPISBAIJ;
2197: B->assembled = PETSC_FALSE;
2198: B->insertmode = NOT_SET_VALUES;
2200: MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);
2201: MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);
2203: /* build local table of row and column ownerships */
2204: PetscMalloc1(b->size+2,&b->rangebs);
2206: /* build cache for off array entries formed */
2207: MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);
2209: b->donotstash = PETSC_FALSE;
2210: b->colmap = NULL;
2211: b->garray = NULL;
2212: b->roworiented = PETSC_TRUE;
2214: /* stuff used in block assembly */
2215: b->barray = 0;
2217: /* stuff used for matrix vector multiply */
2218: b->lvec = 0;
2219: b->Mvctx = 0;
2220: b->slvec0 = 0;
2221: b->slvec0b = 0;
2222: b->slvec1 = 0;
2223: b->slvec1a = 0;
2224: b->slvec1b = 0;
2225: b->sMvctx = 0;
2227: /* stuff for MatGetRow() */
2228: b->rowindices = 0;
2229: b->rowvalues = 0;
2230: b->getrowactive = PETSC_FALSE;
2232: /* hash table stuff */
2233: b->ht = 0;
2234: b->hd = 0;
2235: b->ht_size = 0;
2236: b->ht_flag = PETSC_FALSE;
2237: b->ht_fact = 0;
2238: b->ht_total_ct = 0;
2239: b->ht_insert_ct = 0;
2241: /* stuff for MatCreateSubMatrices_MPIBAIJ_local() */
2242: b->ijonly = PETSC_FALSE;
2244: b->in_loc = 0;
2245: b->v_loc = 0;
2246: b->n_loc = 0;
2248: PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPISBAIJ);
2249: PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPISBAIJ);
2250: PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",MatMPISBAIJSetPreallocation_MPISBAIJ);
2251: PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocationCSR_C",MatMPISBAIJSetPreallocationCSR_MPISBAIJ);
2252: #if defined(PETSC_HAVE_ELEMENTAL)
2253: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_elemental_C",MatConvert_MPISBAIJ_Elemental);
2254: #endif
2256: B->symmetric = PETSC_TRUE;
2257: B->structurally_symmetric = PETSC_TRUE;
2258: B->symmetric_set = PETSC_TRUE;
2259: B->structurally_symmetric_set = PETSC_TRUE;
2260: B->symmetric_eternal = PETSC_TRUE;
2262: B->hermitian = PETSC_FALSE;
2263: B->hermitian_set = PETSC_FALSE;
2265: PetscObjectChangeTypeName((PetscObject)B,MATMPISBAIJ);
2266: PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPISBAIJ matrix 1","Mat");
2267: PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",flg,&flg,NULL);
2268: if (flg) {
2269: PetscReal fact = 1.39;
2270: MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);
2271: PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);
2272: if (fact <= 1.0) fact = 1.39;
2273: MatMPIBAIJSetHashTableFactor(B,fact);
2274: PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);
2275: }
2276: PetscOptionsEnd();
2277: return(0);
2278: }
2280: /*MC
2281: MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices.
2283: This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator,
2284: and MATMPISBAIJ otherwise.
2286: Options Database Keys:
2287: . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions()
2289: Level: beginner
2291: .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ
2292: M*/
2294: /*@C
2295: MatMPISBAIJSetPreallocation - For good matrix assembly performance
2296: the user should preallocate the matrix storage by setting the parameters
2297: d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately,
2298: performance can be increased by more than a factor of 50.
2300: Collective on Mat
2302: Input Parameters:
2303: + B - the matrix
2304: . bs - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
2305: blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
2306: . d_nz - number of block nonzeros per block row in diagonal portion of local
2307: submatrix (same for all local rows)
2308: . d_nnz - array containing the number of block nonzeros in the various block rows
2309: in the upper triangular and diagonal part of the in diagonal portion of the local
2310: (possibly different for each block row) or NULL. If you plan to factor the matrix you must leave room
2311: for the diagonal entry and set a value even if it is zero.
2312: . o_nz - number of block nonzeros per block row in the off-diagonal portion of local
2313: submatrix (same for all local rows).
2314: - o_nnz - array containing the number of nonzeros in the various block rows of the
2315: off-diagonal portion of the local submatrix that is right of the diagonal
2316: (possibly different for each block row) or NULL.
2319: Options Database Keys:
2320: . -mat_no_unroll - uses code that does not unroll the loops in the
2321: block calculations (much slower)
2322: . -mat_block_size - size of the blocks to use
2324: Notes:
2326: If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor
2327: than it must be used on all processors that share the object for that argument.
2329: If the *_nnz parameter is given then the *_nz parameter is ignored
2331: Storage Information:
2332: For a square global matrix we define each processor's diagonal portion
2333: to be its local rows and the corresponding columns (a square submatrix);
2334: each processor's off-diagonal portion encompasses the remainder of the
2335: local matrix (a rectangular submatrix).
2337: The user can specify preallocated storage for the diagonal part of
2338: the local submatrix with either d_nz or d_nnz (not both). Set
2339: d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
2340: memory allocation. Likewise, specify preallocated storage for the
2341: off-diagonal part of the local submatrix with o_nz or o_nnz (not both).
2343: You can call MatGetInfo() to get information on how effective the preallocation was;
2344: for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
2345: You can also run with the option -info and look for messages with the string
2346: malloc in them to see if additional memory allocation was needed.
2348: Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
2349: the figure below we depict these three local rows and all columns (0-11).
2351: .vb
2352: 0 1 2 3 4 5 6 7 8 9 10 11
2353: --------------------------
2354: row 3 |. . . d d d o o o o o o
2355: row 4 |. . . d d d o o o o o o
2356: row 5 |. . . d d d o o o o o o
2357: --------------------------
2358: .ve
2360: Thus, any entries in the d locations are stored in the d (diagonal)
2361: submatrix, and any entries in the o locations are stored in the
2362: o (off-diagonal) submatrix. Note that the d matrix is stored in
2363: MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format.
2365: Now d_nz should indicate the number of block nonzeros per row in the upper triangular
2366: plus the diagonal part of the d matrix,
2367: and o_nz should indicate the number of block nonzeros per row in the o matrix
2369: In general, for PDE problems in which most nonzeros are near the diagonal,
2370: one expects d_nz >> o_nz. For large problems you MUST preallocate memory
2371: or you will get TERRIBLE performance; see the users' manual chapter on
2372: matrices.
2374: Level: intermediate
2376: .keywords: matrix, block, aij, compressed row, sparse, parallel
2378: .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ(), PetscSplitOwnership()
2379: @*/
2380: PetscErrorCode MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
2381: {
2388: PetscTryMethod(B,"MatMPISBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,bs,d_nz,d_nnz,o_nz,o_nnz));
2389: return(0);
2390: }
2392: /*@C
2393: MatCreateSBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format
2394: (block compressed row). For good matrix assembly performance
2395: the user should preallocate the matrix storage by setting the parameters
2396: d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately,
2397: performance can be increased by more than a factor of 50.
2399: Collective on MPI_Comm
2401: Input Parameters:
2402: + comm - MPI communicator
2403: . bs - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
2404: blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
2405: . m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
2406: This value should be the same as the local size used in creating the
2407: y vector for the matrix-vector product y = Ax.
2408: . n - number of local columns (or PETSC_DECIDE to have calculated if N is given)
2409: This value should be the same as the local size used in creating the
2410: x vector for the matrix-vector product y = Ax.
2411: . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
2412: . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
2413: . d_nz - number of block nonzeros per block row in diagonal portion of local
2414: submatrix (same for all local rows)
2415: . d_nnz - array containing the number of block nonzeros in the various block rows
2416: in the upper triangular portion of the in diagonal portion of the local
2417: (possibly different for each block block row) or NULL.
2418: If you plan to factor the matrix you must leave room for the diagonal entry and
2419: set its value even if it is zero.
2420: . o_nz - number of block nonzeros per block row in the off-diagonal portion of local
2421: submatrix (same for all local rows).
2422: - o_nnz - array containing the number of nonzeros in the various block rows of the
2423: off-diagonal portion of the local submatrix (possibly different for
2424: each block row) or NULL.
2426: Output Parameter:
2427: . A - the matrix
2429: Options Database Keys:
2430: . -mat_no_unroll - uses code that does not unroll the loops in the
2431: block calculations (much slower)
2432: . -mat_block_size - size of the blocks to use
2433: . -mat_mpi - use the parallel matrix data structures even on one processor
2434: (defaults to using SeqBAIJ format on one processor)
2436: It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
2437: MatXXXXSetPreallocation() paradgm instead of this routine directly.
2438: [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]
2440: Notes:
2441: The number of rows and columns must be divisible by blocksize.
2442: This matrix type does not support complex Hermitian operation.
2444: The user MUST specify either the local or global matrix dimensions
2445: (possibly both).
2447: If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor
2448: than it must be used on all processors that share the object for that argument.
2450: If the *_nnz parameter is given then the *_nz parameter is ignored
2452: Storage Information:
2453: For a square global matrix we define each processor's diagonal portion
2454: to be its local rows and the corresponding columns (a square submatrix);
2455: each processor's off-diagonal portion encompasses the remainder of the
2456: local matrix (a rectangular submatrix).
2458: The user can specify preallocated storage for the diagonal part of
2459: the local submatrix with either d_nz or d_nnz (not both). Set
2460: d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
2461: memory allocation. Likewise, specify preallocated storage for the
2462: off-diagonal part of the local submatrix with o_nz or o_nnz (not both).
2464: Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
2465: the figure below we depict these three local rows and all columns (0-11).
2467: .vb
2468: 0 1 2 3 4 5 6 7 8 9 10 11
2469: --------------------------
2470: row 3 |. . . d d d o o o o o o
2471: row 4 |. . . d d d o o o o o o
2472: row 5 |. . . d d d o o o o o o
2473: --------------------------
2474: .ve
2476: Thus, any entries in the d locations are stored in the d (diagonal)
2477: submatrix, and any entries in the o locations are stored in the
2478: o (off-diagonal) submatrix. Note that the d matrix is stored in
2479: MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format.
2481: Now d_nz should indicate the number of block nonzeros per row in the upper triangular
2482: plus the diagonal part of the d matrix,
2483: and o_nz should indicate the number of block nonzeros per row in the o matrix.
2484: In general, for PDE problems in which most nonzeros are near the diagonal,
2485: one expects d_nz >> o_nz. For large problems you MUST preallocate memory
2486: or you will get TERRIBLE performance; see the users' manual chapter on
2487: matrices.
2489: Level: intermediate
2491: .keywords: matrix, block, aij, compressed row, sparse, parallel
2493: .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ()
2494: @*/
2496: PetscErrorCode MatCreateSBAIJ(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[],Mat *A)
2497: {
2499: PetscMPIInt size;
2502: MatCreate(comm,A);
2503: MatSetSizes(*A,m,n,M,N);
2504: MPI_Comm_size(comm,&size);
2505: if (size > 1) {
2506: MatSetType(*A,MATMPISBAIJ);
2507: MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);
2508: } else {
2509: MatSetType(*A,MATSEQSBAIJ);
2510: MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);
2511: }
2512: return(0);
2513: }
2516: static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
2517: {
2518: Mat mat;
2519: Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data;
2521: PetscInt len=0,nt,bs=matin->rmap->bs,mbs=oldmat->mbs;
2522: PetscScalar *array;
2525: *newmat = 0;
2527: MatCreate(PetscObjectComm((PetscObject)matin),&mat);
2528: MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
2529: MatSetType(mat,((PetscObject)matin)->type_name);
2530: PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));
2531: PetscLayoutReference(matin->rmap,&mat->rmap);
2532: PetscLayoutReference(matin->cmap,&mat->cmap);
2534: mat->factortype = matin->factortype;
2535: mat->preallocated = PETSC_TRUE;
2536: mat->assembled = PETSC_TRUE;
2537: mat->insertmode = NOT_SET_VALUES;
2539: a = (Mat_MPISBAIJ*)mat->data;
2540: a->bs2 = oldmat->bs2;
2541: a->mbs = oldmat->mbs;
2542: a->nbs = oldmat->nbs;
2543: a->Mbs = oldmat->Mbs;
2544: a->Nbs = oldmat->Nbs;
2547: a->size = oldmat->size;
2548: a->rank = oldmat->rank;
2549: a->donotstash = oldmat->donotstash;
2550: a->roworiented = oldmat->roworiented;
2551: a->rowindices = 0;
2552: a->rowvalues = 0;
2553: a->getrowactive = PETSC_FALSE;
2554: a->barray = 0;
2555: a->rstartbs = oldmat->rstartbs;
2556: a->rendbs = oldmat->rendbs;
2557: a->cstartbs = oldmat->cstartbs;
2558: a->cendbs = oldmat->cendbs;
2560: /* hash table stuff */
2561: a->ht = 0;
2562: a->hd = 0;
2563: a->ht_size = 0;
2564: a->ht_flag = oldmat->ht_flag;
2565: a->ht_fact = oldmat->ht_fact;
2566: a->ht_total_ct = 0;
2567: a->ht_insert_ct = 0;
2569: PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+2)*sizeof(PetscInt));
2570: if (oldmat->colmap) {
2571: #if defined(PETSC_USE_CTABLE)
2572: PetscTableCreateCopy(oldmat->colmap,&a->colmap);
2573: #else
2574: PetscMalloc1(a->Nbs,&a->colmap);
2575: PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));
2576: PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));
2577: #endif
2578: } else a->colmap = 0;
2580: if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) {
2581: PetscMalloc1(len,&a->garray);
2582: PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));
2583: PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));
2584: } else a->garray = 0;
2586: MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);
2587: VecDuplicate(oldmat->lvec,&a->lvec);
2588: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);
2589: VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
2590: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);
2592: VecDuplicate(oldmat->slvec0,&a->slvec0);
2593: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);
2594: VecDuplicate(oldmat->slvec1,&a->slvec1);
2595: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);
2597: VecGetLocalSize(a->slvec1,&nt);
2598: VecGetArray(a->slvec1,&array);
2599: VecCreateSeqWithArray(PETSC_COMM_SELF,1,bs*mbs,array,&a->slvec1a);
2600: VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec1b);
2601: VecRestoreArray(a->slvec1,&array);
2602: VecGetArray(a->slvec0,&array);
2603: VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec0b);
2604: VecRestoreArray(a->slvec0,&array);
2605: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);
2606: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);
2607: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0b);
2608: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1a);
2609: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1b);
2611: /* VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */
2612: PetscObjectReference((PetscObject)oldmat->sMvctx);
2613: a->sMvctx = oldmat->sMvctx;
2614: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->sMvctx);
2616: MatDuplicate(oldmat->A,cpvalues,&a->A);
2617: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
2618: MatDuplicate(oldmat->B,cpvalues,&a->B);
2619: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);
2620: PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
2621: *newmat = mat;
2622: return(0);
2623: }
2625: PetscErrorCode MatLoad_MPISBAIJ(Mat newmat,PetscViewer viewer)
2626: {
2628: PetscInt i,nz,j,rstart,rend;
2629: PetscScalar *vals,*buf;
2630: MPI_Comm comm;
2631: MPI_Status status;
2632: PetscMPIInt rank,size,tag = ((PetscObject)viewer)->tag,*sndcounts = 0,*browners,maxnz,*rowners,mmbs;
2633: PetscInt header[4],*rowlengths = 0,M,N,m,*cols,*locrowlens;
2634: PetscInt *procsnz = 0,jj,*mycols,*ibuf;
2635: PetscInt bs = newmat->rmap->bs,Mbs,mbs,extra_rows;
2636: PetscInt *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount;
2637: PetscInt dcount,kmax,k,nzcount,tmp;
2638: int fd;
2641: /* force binary viewer to load .info file if it has not yet done so */
2642: PetscViewerSetUp(viewer);
2643: PetscObjectGetComm((PetscObject)viewer,&comm);
2644: PetscOptionsBegin(comm,NULL,"Options for loading MPISBAIJ matrix 2","Mat");
2645: PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);
2646: PetscOptionsEnd();
2647: if (bs < 0) bs = 1;
2649: MPI_Comm_size(comm,&size);
2650: MPI_Comm_rank(comm,&rank);
2651: PetscViewerBinaryGetDescriptor(viewer,&fd);
2652: if (!rank) {
2653: PetscBinaryRead(fd,(char*)header,4,PETSC_INT);
2654: if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
2655: if (header[3] < 0) SETERRQ(PetscObjectComm((PetscObject)newmat),PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ");
2656: }
2658: MPI_Bcast(header+1,3,MPIU_INT,0,comm);
2659: M = header[1];
2660: N = header[2];
2662: /* If global sizes are set, check if they are consistent with that given in the file */
2663: 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);
2664: 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);
2666: if (M != N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only do square matrices");
2668: /*
2669: This code adds extra rows to make sure the number of rows is
2670: divisible by the blocksize
2671: */
2672: Mbs = M/bs;
2673: extra_rows = bs - M + bs*(Mbs);
2674: if (extra_rows == bs) extra_rows = 0;
2675: else Mbs++;
2676: if (extra_rows &&!rank) {
2677: PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");
2678: }
2680: /* determine ownership of all rows */
2681: if (newmat->rmap->n < 0) { /* PETSC_DECIDE */
2682: mbs = Mbs/size + ((Mbs % size) > rank);
2683: m = mbs*bs;
2684: } else { /* User Set */
2685: m = newmat->rmap->n;
2686: mbs = m/bs;
2687: }
2688: PetscMalloc2(size+1,&rowners,size+1,&browners);
2689: PetscMPIIntCast(mbs,&mmbs);
2690: MPI_Allgather(&mmbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);
2691: rowners[0] = 0;
2692: for (i=2; i<=size; i++) rowners[i] += rowners[i-1];
2693: for (i=0; i<=size; i++) browners[i] = rowners[i]*bs;
2694: rstart = rowners[rank];
2695: rend = rowners[rank+1];
2697: /* distribute row lengths to all processors */
2698: PetscMalloc1((rend-rstart)*bs,&locrowlens);
2699: if (!rank) {
2700: PetscMalloc1(M+extra_rows,&rowlengths);
2701: PetscBinaryRead(fd,rowlengths,M,PETSC_INT);
2702: for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1;
2703: PetscMalloc1(size,&sndcounts);
2704: for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i];
2705: MPI_Scatterv(rowlengths,sndcounts,browners,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);
2706: PetscFree(sndcounts);
2707: } else {
2708: MPI_Scatterv(0,0,0,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);
2709: }
2711: if (!rank) { /* procs[0] */
2712: /* calculate the number of nonzeros on each processor */
2713: PetscMalloc1(size,&procsnz);
2714: PetscMemzero(procsnz,size*sizeof(PetscInt));
2715: for (i=0; i<size; i++) {
2716: for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) {
2717: procsnz[i] += rowlengths[j];
2718: }
2719: }
2720: PetscFree(rowlengths);
2722: /* determine max buffer needed and allocate it */
2723: maxnz = 0;
2724: for (i=0; i<size; i++) {
2725: maxnz = PetscMax(maxnz,procsnz[i]);
2726: }
2727: PetscMalloc1(maxnz,&cols);
2729: /* read in my part of the matrix column indices */
2730: nz = procsnz[0];
2731: PetscMalloc1(nz,&ibuf);
2732: mycols = ibuf;
2733: if (size == 1) nz -= extra_rows;
2734: PetscBinaryRead(fd,mycols,nz,PETSC_INT);
2735: if (size == 1) {
2736: for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i;
2737: }
2739: /* read in every ones (except the last) and ship off */
2740: for (i=1; i<size-1; i++) {
2741: nz = procsnz[i];
2742: PetscBinaryRead(fd,cols,nz,PETSC_INT);
2743: MPI_Send(cols,nz,MPIU_INT,i,tag,comm);
2744: }
2745: /* read in the stuff for the last proc */
2746: if (size != 1) {
2747: nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */
2748: PetscBinaryRead(fd,cols,nz,PETSC_INT);
2749: for (i=0; i<extra_rows; i++) cols[nz+i] = M+i;
2750: MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);
2751: }
2752: PetscFree(cols);
2753: } else { /* procs[i], i>0 */
2754: /* determine buffer space needed for message */
2755: nz = 0;
2756: for (i=0; i<m; i++) nz += locrowlens[i];
2757: PetscMalloc1(nz,&ibuf);
2758: mycols = ibuf;
2759: /* receive message of column indices*/
2760: MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);
2761: MPI_Get_count(&status,MPIU_INT,&maxnz);
2762: if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");
2763: }
2765: /* loop over local rows, determining number of off diagonal entries */
2766: PetscMalloc2(rend-rstart,&dlens,rend-rstart,&odlens);
2767: PetscMalloc3(Mbs,&mask,Mbs,&masked1,Mbs,&masked2);
2768: PetscMemzero(mask,Mbs*sizeof(PetscInt));
2769: PetscMemzero(masked1,Mbs*sizeof(PetscInt));
2770: PetscMemzero(masked2,Mbs*sizeof(PetscInt));
2771: rowcount = 0;
2772: nzcount = 0;
2773: for (i=0; i<mbs; i++) {
2774: dcount = 0;
2775: odcount = 0;
2776: for (j=0; j<bs; j++) {
2777: kmax = locrowlens[rowcount];
2778: for (k=0; k<kmax; k++) {
2779: tmp = mycols[nzcount++]/bs; /* block col. index */
2780: if (!mask[tmp]) {
2781: mask[tmp] = 1;
2782: if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */
2783: else masked1[dcount++] = tmp; /* entry in diag portion */
2784: }
2785: }
2786: rowcount++;
2787: }
2789: dlens[i] = dcount; /* d_nzz[i] */
2790: odlens[i] = odcount; /* o_nzz[i] */
2792: /* zero out the mask elements we set */
2793: for (j=0; j<dcount; j++) mask[masked1[j]] = 0;
2794: for (j=0; j<odcount; j++) mask[masked2[j]] = 0;
2795: }
2796: MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);
2797: MatMPISBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);
2798: MatSetOption(newmat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE);
2800: if (!rank) {
2801: PetscMalloc1(maxnz,&buf);
2802: /* read in my part of the matrix numerical values */
2803: nz = procsnz[0];
2804: vals = buf;
2805: mycols = ibuf;
2806: if (size == 1) nz -= extra_rows;
2807: PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
2808: if (size == 1) {
2809: for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0;
2810: }
2812: /* insert into matrix */
2813: jj = rstart*bs;
2814: for (i=0; i<m; i++) {
2815: MatSetValues(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);
2816: mycols += locrowlens[i];
2817: vals += locrowlens[i];
2818: jj++;
2819: }
2821: /* read in other processors (except the last one) and ship out */
2822: for (i=1; i<size-1; i++) {
2823: nz = procsnz[i];
2824: vals = buf;
2825: PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
2826: MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);
2827: }
2828: /* the last proc */
2829: if (size != 1) {
2830: nz = procsnz[i] - extra_rows;
2831: vals = buf;
2832: PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);
2833: for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0;
2834: MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);
2835: }
2836: PetscFree(procsnz);
2838: } else {
2839: /* receive numeric values */
2840: PetscMalloc1(nz,&buf);
2842: /* receive message of values*/
2843: vals = buf;
2844: mycols = ibuf;
2845: MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm,&status);
2846: MPI_Get_count(&status,MPIU_SCALAR,&maxnz);
2847: if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");
2849: /* insert into matrix */
2850: jj = rstart*bs;
2851: for (i=0; i<m; i++) {
2852: MatSetValues_MPISBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);
2853: mycols += locrowlens[i];
2854: vals += locrowlens[i];
2855: jj++;
2856: }
2857: }
2859: PetscFree(locrowlens);
2860: PetscFree(buf);
2861: PetscFree(ibuf);
2862: PetscFree2(rowners,browners);
2863: PetscFree2(dlens,odlens);
2864: PetscFree3(mask,masked1,masked2);
2865: MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);
2866: MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);
2867: return(0);
2868: }
2870: /*XXXXX@
2871: MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable.
2873: Input Parameters:
2874: . mat - the matrix
2875: . fact - factor
2877: Not Collective on Mat, each process can have a different hash factor
2879: Level: advanced
2881: Notes:
2882: This can also be set by the command line option: -mat_use_hash_table fact
2884: .keywords: matrix, hashtable, factor, HT
2886: .seealso: MatSetOption()
2887: @XXXXX*/
2890: PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat A,Vec v,PetscInt idx[])
2891: {
2892: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
2893: Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data;
2894: PetscReal atmp;
2895: PetscReal *work,*svalues,*rvalues;
2897: PetscInt i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol;
2898: PetscMPIInt rank,size;
2899: PetscInt *rowners_bs,dest,count,source;
2900: PetscScalar *va;
2901: MatScalar *ba;
2902: MPI_Status stat;
2905: if (idx) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Send email to petsc-maint@mcs.anl.gov");
2906: MatGetRowMaxAbs(a->A,v,NULL);
2907: VecGetArray(v,&va);
2909: MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);
2910: MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);
2912: bs = A->rmap->bs;
2913: mbs = a->mbs;
2914: Mbs = a->Mbs;
2915: ba = b->a;
2916: bi = b->i;
2917: bj = b->j;
2919: /* find ownerships */
2920: rowners_bs = A->rmap->range;
2922: /* each proc creates an array to be distributed */
2923: PetscMalloc1(bs*Mbs,&work);
2924: PetscMemzero(work,bs*Mbs*sizeof(PetscReal));
2926: /* row_max for B */
2927: if (rank != size-1) {
2928: for (i=0; i<mbs; i++) {
2929: ncols = bi[1] - bi[0]; bi++;
2930: brow = bs*i;
2931: for (j=0; j<ncols; j++) {
2932: bcol = bs*(*bj);
2933: for (kcol=0; kcol<bs; kcol++) {
2934: col = bcol + kcol; /* local col index */
2935: col += rowners_bs[rank+1]; /* global col index */
2936: for (krow=0; krow<bs; krow++) {
2937: atmp = PetscAbsScalar(*ba); ba++;
2938: row = brow + krow; /* local row index */
2939: if (PetscRealPart(va[row]) < atmp) va[row] = atmp;
2940: if (work[col] < atmp) work[col] = atmp;
2941: }
2942: }
2943: bj++;
2944: }
2945: }
2947: /* send values to its owners */
2948: for (dest=rank+1; dest<size; dest++) {
2949: svalues = work + rowners_bs[dest];
2950: count = rowners_bs[dest+1]-rowners_bs[dest];
2951: MPI_Send(svalues,count,MPIU_REAL,dest,rank,PetscObjectComm((PetscObject)A));
2952: }
2953: }
2955: /* receive values */
2956: if (rank) {
2957: rvalues = work;
2958: count = rowners_bs[rank+1]-rowners_bs[rank];
2959: for (source=0; source<rank; source++) {
2960: MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,PetscObjectComm((PetscObject)A),&stat);
2961: /* process values */
2962: for (i=0; i<count; i++) {
2963: if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i];
2964: }
2965: }
2966: }
2968: VecRestoreArray(v,&va);
2969: PetscFree(work);
2970: return(0);
2971: }
2973: PetscErrorCode MatSOR_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
2974: {
2975: Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data;
2976: PetscErrorCode ierr;
2977: PetscInt mbs=mat->mbs,bs=matin->rmap->bs;
2978: PetscScalar *x,*ptr,*from;
2979: Vec bb1;
2980: const PetscScalar *b;
2983: if (its <= 0 || lits <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
2984: if (bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented");
2986: if (flag == SOR_APPLY_UPPER) {
2987: (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
2988: return(0);
2989: }
2991: if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
2992: if (flag & SOR_ZERO_INITIAL_GUESS) {
2993: (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);
2994: its--;
2995: }
2997: VecDuplicate(bb,&bb1);
2998: while (its--) {
3000: /* lower triangular part: slvec0b = - B^T*xx */
3001: (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);
3003: /* copy xx into slvec0a */
3004: VecGetArray(mat->slvec0,&ptr);
3005: VecGetArray(xx,&x);
3006: PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));
3007: VecRestoreArray(mat->slvec0,&ptr);
3009: VecScale(mat->slvec0,-1.0);
3011: /* copy bb into slvec1a */
3012: VecGetArray(mat->slvec1,&ptr);
3013: VecGetArrayRead(bb,&b);
3014: PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));
3015: VecRestoreArray(mat->slvec1,&ptr);
3017: /* set slvec1b = 0 */
3018: VecSet(mat->slvec1b,0.0);
3020: VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
3021: VecRestoreArray(xx,&x);
3022: VecRestoreArrayRead(bb,&b);
3023: VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
3025: /* upper triangular part: bb1 = bb1 - B*x */
3026: (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);
3028: /* local diagonal sweep */
3029: (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);
3030: }
3031: VecDestroy(&bb1);
3032: } else if ((flag & SOR_LOCAL_FORWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) {
3033: (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
3034: } else if ((flag & SOR_LOCAL_BACKWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) {
3035: (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
3036: } else if (flag & SOR_EISENSTAT) {
3037: Vec xx1;
3038: PetscBool hasop;
3039: const PetscScalar *diag;
3040: PetscScalar *sl,scale = (omega - 2.0)/omega;
3041: PetscInt i,n;
3043: if (!mat->xx1) {
3044: VecDuplicate(bb,&mat->xx1);
3045: VecDuplicate(bb,&mat->bb1);
3046: }
3047: xx1 = mat->xx1;
3048: bb1 = mat->bb1;
3050: (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);
3052: if (!mat->diag) {
3053: /* this is wrong for same matrix with new nonzero values */
3054: MatCreateVecs(matin,&mat->diag,NULL);
3055: MatGetDiagonal(matin,mat->diag);
3056: }
3057: MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);
3059: if (hasop) {
3060: MatMultDiagonalBlock(matin,xx,bb1);
3061: VecAYPX(mat->slvec1a,scale,bb);
3062: } else {
3063: /*
3064: These two lines are replaced by code that may be a bit faster for a good compiler
3065: VecPointwiseMult(mat->slvec1a,mat->diag,xx);
3066: VecAYPX(mat->slvec1a,scale,bb);
3067: */
3068: VecGetArray(mat->slvec1a,&sl);
3069: VecGetArrayRead(mat->diag,&diag);
3070: VecGetArrayRead(bb,&b);
3071: VecGetArray(xx,&x);
3072: VecGetLocalSize(xx,&n);
3073: if (omega == 1.0) {
3074: for (i=0; i<n; i++) sl[i] = b[i] - diag[i]*x[i];
3075: PetscLogFlops(2.0*n);
3076: } else {
3077: for (i=0; i<n; i++) sl[i] = b[i] + scale*diag[i]*x[i];
3078: PetscLogFlops(3.0*n);
3079: }
3080: VecRestoreArray(mat->slvec1a,&sl);
3081: VecRestoreArrayRead(mat->diag,&diag);
3082: VecRestoreArrayRead(bb,&b);
3083: VecRestoreArray(xx,&x);
3084: }
3086: /* multiply off-diagonal portion of matrix */
3087: VecSet(mat->slvec1b,0.0);
3088: (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);
3089: VecGetArray(mat->slvec0,&from);
3090: VecGetArray(xx,&x);
3091: PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
3092: VecRestoreArray(mat->slvec0,&from);
3093: VecRestoreArray(xx,&x);
3094: VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
3095: VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
3096: (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,mat->slvec1a);
3098: /* local sweep */
3099: (*mat->A->ops->sor)(mat->A,mat->slvec1a,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);
3100: VecAXPY(xx,1.0,xx1);
3101: } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format");
3102: return(0);
3103: }
3105: PetscErrorCode MatSOR_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
3106: {
3107: Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data;
3109: Vec lvec1,bb1;
3112: if (its <= 0 || lits <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
3113: if (matin->rmap->bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented");
3115: if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
3116: if (flag & SOR_ZERO_INITIAL_GUESS) {
3117: (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);
3118: its--;
3119: }
3121: VecDuplicate(mat->lvec,&lvec1);
3122: VecDuplicate(bb,&bb1);
3123: while (its--) {
3124: VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
3126: /* lower diagonal part: bb1 = bb - B^T*xx */
3127: (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);
3128: VecScale(lvec1,-1.0);
3130: VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
3131: VecCopy(bb,bb1);
3132: VecScatterBegin(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);
3134: /* upper diagonal part: bb1 = bb1 - B*x */
3135: VecScale(mat->lvec,-1.0);
3136: (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);
3138: VecScatterEnd(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);
3140: /* diagonal sweep */
3141: (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);
3142: }
3143: VecDestroy(&lvec1);
3144: VecDestroy(&bb1);
3145: } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format");
3146: return(0);
3147: }
3149: /*@
3150: MatCreateMPISBAIJWithArrays - creates a MPI SBAIJ matrix using arrays that contain in standard
3151: CSR format the local rows.
3153: Collective on MPI_Comm
3155: Input Parameters:
3156: + comm - MPI communicator
3157: . bs - the block size, only a block size of 1 is supported
3158: . m - number of local rows (Cannot be PETSC_DECIDE)
3159: . n - This value should be the same as the local size used in creating the
3160: x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
3161: calculated if N is given) For square matrices n is almost always m.
3162: . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
3163: . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
3164: . i - row indices
3165: . j - column indices
3166: - a - matrix values
3168: Output Parameter:
3169: . mat - the matrix
3171: Level: intermediate
3173: Notes:
3174: The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
3175: thus you CANNOT change the matrix entries by changing the values of a[] after you have
3176: called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.
3178: The i and j indices are 0 based, and i indices are indices corresponding to the local j array.
3180: .keywords: matrix, aij, compressed row, sparse, parallel
3182: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
3183: MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays()
3184: @*/
3185: PetscErrorCode MatCreateMPISBAIJWithArrays(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat)
3186: {
3191: if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
3192: if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
3193: MatCreate(comm,mat);
3194: MatSetSizes(*mat,m,n,M,N);
3195: MatSetType(*mat,MATMPISBAIJ);
3196: MatMPISBAIJSetPreallocationCSR(*mat,bs,i,j,a);
3197: return(0);
3198: }
3201: /*@C
3202: MatMPISBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format
3203: (the default parallel PETSc format).
3205: Collective on MPI_Comm
3207: Input Parameters:
3208: + B - the matrix
3209: . bs - the block size
3210: . i - the indices into j for the start of each local row (starts with zero)
3211: . j - the column indices for each local row (starts with zero) these must be sorted for each row
3212: - v - optional values in the matrix
3214: Level: developer
3216: .keywords: matrix, aij, compressed row, sparse, parallel
3218: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ
3219: @*/
3220: PetscErrorCode MatMPISBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
3221: {
3225: PetscTryMethod(B,"MatMPISBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));
3226: return(0);
3227: }
3229: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPISBAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
3230: {
3232: PetscInt m,N,i,rstart,nnz,Ii,bs,cbs;
3233: PetscInt *indx;
3234: PetscScalar *values;
3237: MatGetSize(inmat,&m,&N);
3238: if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */
3239: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)inmat->data;
3240: PetscInt *dnz,*onz,sum,bs,cbs,mbs,Nbs;
3241: PetscInt *bindx,rmax=a->rmax,j;
3242:
3243: MatGetBlockSizes(inmat,&bs,&cbs);
3244: mbs = m/bs; Nbs = N/cbs;
3245: if (n == PETSC_DECIDE) {
3246: PetscSplitOwnership(comm,&n,&Nbs);
3247: }
3248: /* Check sum(n) = Nbs */
3249: MPIU_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);
3250: if (sum != Nbs) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",Nbs);
3252: MPI_Scan(&mbs, &rstart,1,MPIU_INT,MPI_SUM,comm);
3253: rstart -= mbs;
3255: PetscMalloc1(rmax,&bindx);
3256: MatPreallocateInitialize(comm,mbs,n,dnz,onz);
3257: MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
3258: for (i=0; i<mbs; i++) {
3259: MatGetRow_SeqSBAIJ(inmat,i*bs,&nnz,&indx,NULL); /* non-blocked nnz and indx */
3260: nnz = nnz/bs;
3261: for (j=0; j<nnz; j++) bindx[j] = indx[j*bs]/bs;
3262: MatPreallocateSet(i+rstart,nnz,bindx,dnz,onz);
3263: MatRestoreRow_SeqSBAIJ(inmat,i*bs,&nnz,&indx,NULL);
3264: }
3265: MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
3266: PetscFree(bindx);
3268: MatCreate(comm,outmat);
3269: MatSetSizes(*outmat,m,n*bs,PETSC_DETERMINE,PETSC_DETERMINE);
3270: MatSetBlockSizes(*outmat,bs,cbs);
3271: MatSetType(*outmat,MATMPISBAIJ);
3272: MatMPISBAIJSetPreallocation(*outmat,bs,0,dnz,0,onz);
3273: MatPreallocateFinalize(dnz,onz);
3274: }
3275:
3276: /* numeric phase */
3277: MatGetBlockSizes(inmat,&bs,&cbs);
3278: MatGetOwnershipRange(*outmat,&rstart,NULL);
3280: MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
3281: for (i=0; i<m; i++) {
3282: MatGetRow_SeqSBAIJ(inmat,i,&nnz,&indx,&values);
3283: Ii = i + rstart;
3284: MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);
3285: MatRestoreRow_SeqSBAIJ(inmat,i,&nnz,&indx,&values);
3286: }
3287: MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
3288: MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);
3289: MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);
3290: return(0);
3291: }