Actual source code: mpisbaij.c
petsc-3.14.6 2021-03-30
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: #if defined(PETSC_HAVE_SCALAPACK)
11: PETSC_INTERN PetscErrorCode MatConvert_SBAIJ_ScaLAPACK(Mat,MatType,MatReuse,Mat*);
12: #endif
14: /* This could be moved to matimpl.h */
15: static PetscErrorCode MatPreallocateWithMats_Private(Mat B, PetscInt nm, Mat X[], PetscBool symm[], PetscBool fill)
16: {
17: Mat preallocator;
18: PetscInt r,rstart,rend;
19: PetscInt bs,i,m,n,M,N;
20: PetscBool cong = PETSC_TRUE;
26: for (i = 0; i < nm; i++) {
28: PetscLayoutCompare(B->rmap,X[i]->rmap,&cong);
29: if (!cong) SETERRQ(PetscObjectComm((PetscObject)B),PETSC_ERR_SUP,"Not for different layouts");
30: }
32: MatGetBlockSize(B,&bs);
33: MatGetSize(B,&M,&N);
34: MatGetLocalSize(B,&m,&n);
35: MatCreate(PetscObjectComm((PetscObject)B),&preallocator);
36: MatSetType(preallocator,MATPREALLOCATOR);
37: MatSetBlockSize(preallocator,bs);
38: MatSetSizes(preallocator,m,n,M,N);
39: MatSetUp(preallocator);
40: MatGetOwnershipRange(preallocator,&rstart,&rend);
41: for (r = rstart; r < rend; ++r) {
42: PetscInt ncols;
43: const PetscInt *row;
44: const PetscScalar *vals;
46: for (i = 0; i < nm; i++) {
47: MatGetRow(X[i],r,&ncols,&row,&vals);
48: MatSetValues(preallocator,1,&r,ncols,row,vals,INSERT_VALUES);
49: if (symm && symm[i]) {
50: MatSetValues(preallocator,ncols,row,1,&r,vals,INSERT_VALUES);
51: }
52: MatRestoreRow(X[i],r,&ncols,&row,&vals);
53: }
54: }
55: MatAssemblyBegin(preallocator,MAT_FINAL_ASSEMBLY);
56: MatAssemblyEnd(preallocator,MAT_FINAL_ASSEMBLY);
57: MatPreallocatorPreallocate(preallocator,fill,B);
58: MatDestroy(&preallocator);
59: return(0);
60: }
62: PETSC_INTERN PetscErrorCode MatConvert_MPISBAIJ_Basic(Mat A, MatType newtype, MatReuse reuse, Mat *newmat)
63: {
64: Mat B;
66: PetscInt r;
69: if (reuse != MAT_REUSE_MATRIX) {
70: PetscBool symm = PETSC_TRUE,isdense;
71: PetscInt bs;
73: MatCreate(PetscObjectComm((PetscObject)A),&B);
74: MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);
75: MatSetType(B,newtype);
76: MatGetBlockSize(A,&bs);
77: MatSetBlockSize(B,bs);
78: PetscLayoutSetUp(B->rmap);
79: PetscLayoutSetUp(B->cmap);
80: PetscObjectTypeCompareAny((PetscObject)B,&isdense,MATSEQDENSE,MATMPIDENSE,MATSEQDENSECUDA,"");
81: if (!isdense) {
82: MatGetRowUpperTriangular(A);
83: MatPreallocateWithMats_Private(B,1,&A,&symm,PETSC_TRUE);
84: MatRestoreRowUpperTriangular(A);
85: } else {
86: MatSetUp(B);
87: }
88: } else {
89: B = *newmat;
90: MatZeroEntries(B);
91: }
93: MatGetRowUpperTriangular(A);
94: for (r = A->rmap->rstart; r < A->rmap->rend; r++) {
95: PetscInt ncols;
96: const PetscInt *row;
97: const PetscScalar *vals;
99: MatGetRow(A,r,&ncols,&row,&vals);
100: MatSetValues(B,1,&r,ncols,row,vals,INSERT_VALUES);
101: #if defined(PETSC_USE_COMPLEX)
102: if (A->hermitian) {
103: PetscInt i;
104: for (i = 0; i < ncols; i++) {
105: MatSetValue(B,row[i],r,PetscConj(vals[i]),INSERT_VALUES);
106: }
107: } else {
108: MatSetValues(B,ncols,row,1,&r,vals,INSERT_VALUES);
109: }
110: #else
111: MatSetValues(B,ncols,row,1,&r,vals,INSERT_VALUES);
112: #endif
113: MatRestoreRow(A,r,&ncols,&row,&vals);
114: }
115: MatRestoreRowUpperTriangular(A);
116: MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
117: MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
119: if (reuse == MAT_INPLACE_MATRIX) {
120: MatHeaderReplace(A,&B);
121: } else {
122: *newmat = B;
123: }
124: return(0);
125: }
127: PetscErrorCode MatStoreValues_MPISBAIJ(Mat mat)
128: {
129: Mat_MPISBAIJ *aij = (Mat_MPISBAIJ*)mat->data;
133: MatStoreValues(aij->A);
134: MatStoreValues(aij->B);
135: return(0);
136: }
138: PetscErrorCode MatRetrieveValues_MPISBAIJ(Mat mat)
139: {
140: Mat_MPISBAIJ *aij = (Mat_MPISBAIJ*)mat->data;
144: MatRetrieveValues(aij->A);
145: MatRetrieveValues(aij->B);
146: return(0);
147: }
149: #define MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv,orow,ocol) \
150: { \
151: brow = row/bs; \
152: rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \
153: rmax = aimax[brow]; nrow = ailen[brow]; \
154: bcol = col/bs; \
155: ridx = row % bs; cidx = col % bs; \
156: low = 0; high = nrow; \
157: while (high-low > 3) { \
158: t = (low+high)/2; \
159: if (rp[t] > bcol) high = t; \
160: else low = t; \
161: } \
162: for (_i=low; _i<high; _i++) { \
163: if (rp[_i] > bcol) break; \
164: if (rp[_i] == bcol) { \
165: bap = ap + bs2*_i + bs*cidx + ridx; \
166: if (addv == ADD_VALUES) *bap += value; \
167: else *bap = value; \
168: goto a_noinsert; \
169: } \
170: } \
171: if (a->nonew == 1) goto a_noinsert; \
172: 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); \
173: MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \
174: N = nrow++ - 1; \
175: /* shift up all the later entries in this row */ \
176: PetscArraymove(rp+_i+1,rp+_i,N-_i+1); \
177: PetscArraymove(ap+bs2*(_i+1),ap+bs2*_i,bs2*(N-_i+1)); \
178: PetscArrayzero(ap+bs2*_i,bs2); \
179: rp[_i] = bcol; \
180: ap[bs2*_i + bs*cidx + ridx] = value; \
181: A->nonzerostate++;\
182: a_noinsert:; \
183: ailen[brow] = nrow; \
184: }
186: #define MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv,orow,ocol) \
187: { \
188: brow = row/bs; \
189: rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \
190: rmax = bimax[brow]; nrow = bilen[brow]; \
191: bcol = col/bs; \
192: ridx = row % bs; cidx = col % bs; \
193: low = 0; high = nrow; \
194: while (high-low > 3) { \
195: t = (low+high)/2; \
196: if (rp[t] > bcol) high = t; \
197: else low = t; \
198: } \
199: for (_i=low; _i<high; _i++) { \
200: if (rp[_i] > bcol) break; \
201: if (rp[_i] == bcol) { \
202: bap = ap + bs2*_i + bs*cidx + ridx; \
203: if (addv == ADD_VALUES) *bap += value; \
204: else *bap = value; \
205: goto b_noinsert; \
206: } \
207: } \
208: if (b->nonew == 1) goto b_noinsert; \
209: 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); \
210: MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \
211: N = nrow++ - 1; \
212: /* shift up all the later entries in this row */ \
213: PetscArraymove(rp+_i+1,rp+_i,N-_i+1); \
214: PetscArraymove(ap+bs2*(_i+1),ap+bs2*_i,bs2*(N-_i+1)); \
215: PetscArrayzero(ap+bs2*_i,bs2); \
216: rp[_i] = bcol; \
217: ap[bs2*_i + bs*cidx + ridx] = value; \
218: B->nonzerostate++;\
219: b_noinsert:; \
220: bilen[brow] = nrow; \
221: }
223: /* Only add/insert a(i,j) with i<=j (blocks).
224: Any a(i,j) with i>j input by user is ingored or generates an error
225: */
226: PetscErrorCode MatSetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
227: {
228: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
229: MatScalar value;
230: PetscBool roworiented = baij->roworiented;
232: PetscInt i,j,row,col;
233: PetscInt rstart_orig=mat->rmap->rstart;
234: PetscInt rend_orig =mat->rmap->rend,cstart_orig=mat->cmap->rstart;
235: PetscInt cend_orig =mat->cmap->rend,bs=mat->rmap->bs;
237: /* Some Variables required in the macro */
238: Mat A = baij->A;
239: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)(A)->data;
240: PetscInt *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j;
241: MatScalar *aa =a->a;
243: Mat B = baij->B;
244: Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data;
245: PetscInt *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j;
246: MatScalar *ba =b->a;
248: PetscInt *rp,ii,nrow,_i,rmax,N,brow,bcol;
249: PetscInt low,high,t,ridx,cidx,bs2=a->bs2;
250: MatScalar *ap,*bap;
252: /* for stash */
253: PetscInt n_loc, *in_loc = NULL;
254: MatScalar *v_loc = NULL;
257: if (!baij->donotstash) {
258: if (n > baij->n_loc) {
259: PetscFree(baij->in_loc);
260: PetscFree(baij->v_loc);
261: PetscMalloc1(n,&baij->in_loc);
262: PetscMalloc1(n,&baij->v_loc);
264: baij->n_loc = n;
265: }
266: in_loc = baij->in_loc;
267: v_loc = baij->v_loc;
268: }
270: for (i=0; i<m; i++) {
271: if (im[i] < 0) continue;
272: if (PetscUnlikely(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);
273: if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */
274: row = im[i] - rstart_orig; /* local row index */
275: for (j=0; j<n; j++) {
276: if (im[i]/bs > in[j]/bs) {
277: if (a->ignore_ltriangular) {
278: continue; /* ignore lower triangular blocks */
279: } 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)");
280: }
281: if (in[j] >= cstart_orig && in[j] < cend_orig) { /* diag entry (A) */
282: col = in[j] - cstart_orig; /* local col index */
283: brow = row/bs; bcol = col/bs;
284: if (brow > bcol) continue; /* ignore lower triangular blocks of A */
285: if (roworiented) value = v[i*n+j];
286: else value = v[i+j*m];
287: MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv,im[i],in[j]);
288: /* MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv); */
289: } else if (in[j] < 0) continue;
290: 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);
291: else { /* off-diag entry (B) */
292: if (mat->was_assembled) {
293: if (!baij->colmap) {
294: MatCreateColmap_MPIBAIJ_Private(mat);
295: }
296: #if defined(PETSC_USE_CTABLE)
297: PetscTableFind(baij->colmap,in[j]/bs + 1,&col);
298: col = col - 1;
299: #else
300: col = baij->colmap[in[j]/bs] - 1;
301: #endif
302: if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) {
303: MatDisAssemble_MPISBAIJ(mat);
304: col = in[j];
305: /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */
306: B = baij->B;
307: b = (Mat_SeqBAIJ*)(B)->data;
308: bimax= b->imax;bi=b->i;bilen=b->ilen;bj=b->j;
309: ba = b->a;
310: } else col += in[j]%bs;
311: } else col = in[j];
312: if (roworiented) value = v[i*n+j];
313: else value = v[i+j*m];
314: MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv,im[i],in[j]);
315: /* MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv); */
316: }
317: }
318: } else { /* off processor entry */
319: 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]);
320: if (!baij->donotstash) {
321: mat->assembled = PETSC_FALSE;
322: n_loc = 0;
323: for (j=0; j<n; j++) {
324: if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */
325: in_loc[n_loc] = in[j];
326: if (roworiented) {
327: v_loc[n_loc] = v[i*n+j];
328: } else {
329: v_loc[n_loc] = v[j*m+i];
330: }
331: n_loc++;
332: }
333: MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc,PETSC_FALSE);
334: }
335: }
336: }
337: return(0);
338: }
340: PETSC_STATIC_INLINE PetscErrorCode MatSetValuesBlocked_SeqSBAIJ_Inlined(Mat A,PetscInt row,PetscInt col,const PetscScalar v[],InsertMode is,PetscInt orow,PetscInt ocol)
341: {
342: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)A->data;
343: PetscErrorCode ierr;
344: PetscInt *rp,low,high,t,ii,jj,nrow,i,rmax,N;
345: PetscInt *imax =a->imax,*ai=a->i,*ailen=a->ilen;
346: PetscInt *aj =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs;
347: PetscBool roworiented=a->roworiented;
348: const PetscScalar *value = v;
349: MatScalar *ap,*aa = a->a,*bap;
352: if (col < row) {
353: if (a->ignore_ltriangular) return(0); /* ignore lower triangular block */
354: 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)");
355: }
356: rp = aj + ai[row];
357: ap = aa + bs2*ai[row];
358: rmax = imax[row];
359: nrow = ailen[row];
360: value = v;
361: low = 0;
362: high = nrow;
364: while (high-low > 7) {
365: t = (low+high)/2;
366: if (rp[t] > col) high = t;
367: else low = t;
368: }
369: for (i=low; i<high; i++) {
370: if (rp[i] > col) break;
371: if (rp[i] == col) {
372: bap = ap + bs2*i;
373: if (roworiented) {
374: if (is == ADD_VALUES) {
375: for (ii=0; ii<bs; ii++) {
376: for (jj=ii; jj<bs2; jj+=bs) {
377: bap[jj] += *value++;
378: }
379: }
380: } else {
381: for (ii=0; ii<bs; ii++) {
382: for (jj=ii; jj<bs2; jj+=bs) {
383: bap[jj] = *value++;
384: }
385: }
386: }
387: } else {
388: if (is == ADD_VALUES) {
389: for (ii=0; ii<bs; ii++) {
390: for (jj=0; jj<bs; jj++) {
391: *bap++ += *value++;
392: }
393: }
394: } else {
395: for (ii=0; ii<bs; ii++) {
396: for (jj=0; jj<bs; jj++) {
397: *bap++ = *value++;
398: }
399: }
400: }
401: }
402: goto noinsert2;
403: }
404: }
405: if (nonew == 1) goto noinsert2;
406: 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);
407: MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
408: N = nrow++ - 1; high++;
409: /* shift up all the later entries in this row */
410: PetscArraymove(rp+i+1,rp+i,N-i+1);
411: PetscArraymove(ap+bs2*(i+1),ap+bs2*i,bs2*(N-i+1));
412: rp[i] = col;
413: bap = ap + bs2*i;
414: if (roworiented) {
415: for (ii=0; ii<bs; ii++) {
416: for (jj=ii; jj<bs2; jj+=bs) {
417: bap[jj] = *value++;
418: }
419: }
420: } else {
421: for (ii=0; ii<bs; ii++) {
422: for (jj=0; jj<bs; jj++) {
423: *bap++ = *value++;
424: }
425: }
426: }
427: noinsert2:;
428: ailen[row] = nrow;
429: return(0);
430: }
432: /*
433: This routine is exactly duplicated in mpibaij.c
434: */
435: PETSC_STATIC_INLINE PetscErrorCode MatSetValuesBlocked_SeqBAIJ_Inlined(Mat A,PetscInt row,PetscInt col,const PetscScalar v[],InsertMode is,PetscInt orow,PetscInt ocol)
436: {
437: Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
438: PetscInt *rp,low,high,t,ii,jj,nrow,i,rmax,N;
439: PetscInt *imax=a->imax,*ai=a->i,*ailen=a->ilen;
440: PetscErrorCode ierr;
441: PetscInt *aj =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs;
442: PetscBool roworiented=a->roworiented;
443: const PetscScalar *value = v;
444: MatScalar *ap,*aa = a->a,*bap;
447: rp = aj + ai[row];
448: ap = aa + bs2*ai[row];
449: rmax = imax[row];
450: nrow = ailen[row];
451: low = 0;
452: high = nrow;
453: value = v;
454: while (high-low > 7) {
455: t = (low+high)/2;
456: if (rp[t] > col) high = t;
457: else low = t;
458: }
459: for (i=low; i<high; i++) {
460: if (rp[i] > col) break;
461: if (rp[i] == col) {
462: bap = ap + bs2*i;
463: if (roworiented) {
464: if (is == ADD_VALUES) {
465: for (ii=0; ii<bs; ii++) {
466: for (jj=ii; jj<bs2; jj+=bs) {
467: bap[jj] += *value++;
468: }
469: }
470: } else {
471: for (ii=0; ii<bs; ii++) {
472: for (jj=ii; jj<bs2; jj+=bs) {
473: bap[jj] = *value++;
474: }
475: }
476: }
477: } else {
478: if (is == ADD_VALUES) {
479: for (ii=0; ii<bs; ii++,value+=bs) {
480: for (jj=0; jj<bs; jj++) {
481: bap[jj] += value[jj];
482: }
483: bap += bs;
484: }
485: } else {
486: for (ii=0; ii<bs; ii++,value+=bs) {
487: for (jj=0; jj<bs; jj++) {
488: bap[jj] = value[jj];
489: }
490: bap += bs;
491: }
492: }
493: }
494: goto noinsert2;
495: }
496: }
497: if (nonew == 1) goto noinsert2;
498: 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);
499: MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
500: N = nrow++ - 1; high++;
501: /* shift up all the later entries in this row */
502: PetscArraymove(rp+i+1,rp+i,N-i+1);
503: PetscArraymove(ap+bs2*(i+1),ap+bs2*i,bs2*(N-i+1));
504: rp[i] = col;
505: bap = ap + bs2*i;
506: if (roworiented) {
507: for (ii=0; ii<bs; ii++) {
508: for (jj=ii; jj<bs2; jj+=bs) {
509: bap[jj] = *value++;
510: }
511: }
512: } else {
513: for (ii=0; ii<bs; ii++) {
514: for (jj=0; jj<bs; jj++) {
515: *bap++ = *value++;
516: }
517: }
518: }
519: noinsert2:;
520: ailen[row] = nrow;
521: return(0);
522: }
524: /*
525: This routine could be optimized by removing the need for the block copy below and passing stride information
526: to the above inline routines; similarly in MatSetValuesBlocked_MPIBAIJ()
527: */
528: PetscErrorCode MatSetValuesBlocked_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv)
529: {
530: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
531: const MatScalar *value;
532: MatScalar *barray =baij->barray;
533: PetscBool roworiented = baij->roworiented,ignore_ltriangular = ((Mat_SeqSBAIJ*)baij->A->data)->ignore_ltriangular;
534: PetscErrorCode ierr;
535: PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs;
536: PetscInt rend=baij->rendbs,cstart=baij->cstartbs,stepval;
537: PetscInt cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2;
540: if (!barray) {
541: PetscMalloc1(bs2,&barray);
542: baij->barray = barray;
543: }
545: if (roworiented) {
546: stepval = (n-1)*bs;
547: } else {
548: stepval = (m-1)*bs;
549: }
550: for (i=0; i<m; i++) {
551: if (im[i] < 0) continue;
552: if (PetscUnlikelyDebug(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);
553: if (im[i] >= rstart && im[i] < rend) {
554: row = im[i] - rstart;
555: for (j=0; j<n; j++) {
556: if (im[i] > in[j]) {
557: if (ignore_ltriangular) continue; /* ignore lower triangular blocks */
558: 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)");
559: }
560: /* If NumCol = 1 then a copy is not required */
561: if ((roworiented) && (n == 1)) {
562: barray = (MatScalar*) v + i*bs2;
563: } else if ((!roworiented) && (m == 1)) {
564: barray = (MatScalar*) v + j*bs2;
565: } else { /* Here a copy is required */
566: if (roworiented) {
567: value = v + i*(stepval+bs)*bs + j*bs;
568: } else {
569: value = v + j*(stepval+bs)*bs + i*bs;
570: }
571: for (ii=0; ii<bs; ii++,value+=stepval) {
572: for (jj=0; jj<bs; jj++) {
573: *barray++ = *value++;
574: }
575: }
576: barray -=bs2;
577: }
579: if (in[j] >= cstart && in[j] < cend) {
580: col = in[j] - cstart;
581: MatSetValuesBlocked_SeqSBAIJ_Inlined(baij->A,row,col,barray,addv,im[i],in[j]);
582: } else if (in[j] < 0) continue;
583: else if (PetscUnlikelyDebug(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);
584: else {
585: if (mat->was_assembled) {
586: if (!baij->colmap) {
587: MatCreateColmap_MPIBAIJ_Private(mat);
588: }
590: #if defined(PETSC_USE_DEBUG)
591: #if defined(PETSC_USE_CTABLE)
592: { PetscInt data;
593: PetscTableFind(baij->colmap,in[j]+1,&data);
594: if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
595: }
596: #else
597: if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
598: #endif
599: #endif
600: #if defined(PETSC_USE_CTABLE)
601: PetscTableFind(baij->colmap,in[j]+1,&col);
602: col = (col - 1)/bs;
603: #else
604: col = (baij->colmap[in[j]] - 1)/bs;
605: #endif
606: if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
607: MatDisAssemble_MPISBAIJ(mat);
608: col = in[j];
609: }
610: } else col = in[j];
611: MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B,row,col,barray,addv,im[i],in[j]);
612: }
613: }
614: } else {
615: 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]);
616: if (!baij->donotstash) {
617: if (roworiented) {
618: MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
619: } else {
620: MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
621: }
622: }
623: }
624: }
625: return(0);
626: }
628: PetscErrorCode MatGetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
629: {
630: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
632: PetscInt bs = mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend;
633: PetscInt bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data;
636: for (i=0; i<m; i++) {
637: if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]); */
638: if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1);
639: if (idxm[i] >= bsrstart && idxm[i] < bsrend) {
640: row = idxm[i] - bsrstart;
641: for (j=0; j<n; j++) {
642: if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column %D",idxn[j]); */
643: if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1);
644: if (idxn[j] >= bscstart && idxn[j] < bscend) {
645: col = idxn[j] - bscstart;
646: MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);
647: } else {
648: if (!baij->colmap) {
649: MatCreateColmap_MPIBAIJ_Private(mat);
650: }
651: #if defined(PETSC_USE_CTABLE)
652: PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);
653: data--;
654: #else
655: data = baij->colmap[idxn[j]/bs]-1;
656: #endif
657: if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0;
658: else {
659: col = data + idxn[j]%bs;
660: MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);
661: }
662: }
663: }
664: } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
665: }
666: return(0);
667: }
669: PetscErrorCode MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm)
670: {
671: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
673: PetscReal sum[2],*lnorm2;
676: if (baij->size == 1) {
677: MatNorm(baij->A,type,norm);
678: } else {
679: if (type == NORM_FROBENIUS) {
680: PetscMalloc1(2,&lnorm2);
681: MatNorm(baij->A,type,lnorm2);
682: *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++; /* squar power of norm(A) */
683: MatNorm(baij->B,type,lnorm2);
684: *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--; /* squar power of norm(B) */
685: MPIU_Allreduce(lnorm2,sum,2,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
686: *norm = PetscSqrtReal(sum[0] + 2*sum[1]);
687: PetscFree(lnorm2);
688: } else if (type == NORM_INFINITY || type == NORM_1) { /* max row/column sum */
689: Mat_SeqSBAIJ *amat=(Mat_SeqSBAIJ*)baij->A->data;
690: Mat_SeqBAIJ *bmat=(Mat_SeqBAIJ*)baij->B->data;
691: PetscReal *rsum,*rsum2,vabs;
692: PetscInt *jj,*garray=baij->garray,rstart=baij->rstartbs,nz;
693: PetscInt brow,bcol,col,bs=baij->A->rmap->bs,row,grow,gcol,mbs=amat->mbs;
694: MatScalar *v;
696: PetscMalloc2(mat->cmap->N,&rsum,mat->cmap->N,&rsum2);
697: PetscArrayzero(rsum,mat->cmap->N);
698: /* Amat */
699: v = amat->a; jj = amat->j;
700: for (brow=0; brow<mbs; brow++) {
701: grow = bs*(rstart + brow);
702: nz = amat->i[brow+1] - amat->i[brow];
703: for (bcol=0; bcol<nz; bcol++) {
704: gcol = bs*(rstart + *jj); jj++;
705: for (col=0; col<bs; col++) {
706: for (row=0; row<bs; row++) {
707: vabs = PetscAbsScalar(*v); v++;
708: rsum[gcol+col] += vabs;
709: /* non-diagonal block */
710: if (bcol > 0 && vabs > 0.0) rsum[grow+row] += vabs;
711: }
712: }
713: }
714: PetscLogFlops(nz*bs*bs);
715: }
716: /* Bmat */
717: v = bmat->a; jj = bmat->j;
718: for (brow=0; brow<mbs; brow++) {
719: grow = bs*(rstart + brow);
720: nz = bmat->i[brow+1] - bmat->i[brow];
721: for (bcol=0; bcol<nz; bcol++) {
722: gcol = bs*garray[*jj]; jj++;
723: for (col=0; col<bs; col++) {
724: for (row=0; row<bs; row++) {
725: vabs = PetscAbsScalar(*v); v++;
726: rsum[gcol+col] += vabs;
727: rsum[grow+row] += vabs;
728: }
729: }
730: }
731: PetscLogFlops(nz*bs*bs);
732: }
733: MPIU_Allreduce(rsum,rsum2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));
734: *norm = 0.0;
735: for (col=0; col<mat->cmap->N; col++) {
736: if (rsum2[col] > *norm) *norm = rsum2[col];
737: }
738: PetscFree2(rsum,rsum2);
739: } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for this norm yet");
740: }
741: return(0);
742: }
744: PetscErrorCode MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode)
745: {
746: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
748: PetscInt nstash,reallocs;
751: if (baij->donotstash || mat->nooffprocentries) return(0);
753: MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
754: MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);
755: MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
756: PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);
757: MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
758: PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
759: return(0);
760: }
762: PetscErrorCode MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode)
763: {
764: Mat_MPISBAIJ *baij=(Mat_MPISBAIJ*)mat->data;
765: Mat_SeqSBAIJ *a =(Mat_SeqSBAIJ*)baij->A->data;
767: PetscInt i,j,rstart,ncols,flg,bs2=baij->bs2;
768: PetscInt *row,*col;
769: PetscBool other_disassembled;
770: PetscMPIInt n;
771: PetscBool r1,r2,r3;
772: MatScalar *val;
774: /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */
776: if (!baij->donotstash && !mat->nooffprocentries) {
777: while (1) {
778: MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);
779: if (!flg) break;
781: for (i=0; i<n;) {
782: /* Now identify the consecutive vals belonging to the same row */
783: for (j=i,rstart=row[j]; j<n; j++) {
784: if (row[j] != rstart) break;
785: }
786: if (j < n) ncols = j-i;
787: else ncols = n-i;
788: /* Now assemble all these values with a single function call */
789: MatSetValues_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i,mat->insertmode);
790: i = j;
791: }
792: }
793: MatStashScatterEnd_Private(&mat->stash);
794: /* Now process the block-stash. Since the values are stashed column-oriented,
795: set the roworiented flag to column oriented, and after MatSetValues()
796: restore the original flags */
797: r1 = baij->roworiented;
798: r2 = a->roworiented;
799: r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented;
801: baij->roworiented = PETSC_FALSE;
802: a->roworiented = PETSC_FALSE;
804: ((Mat_SeqBAIJ*)baij->B->data)->roworiented = PETSC_FALSE; /* b->roworinted */
805: while (1) {
806: MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);
807: if (!flg) break;
809: for (i=0; i<n;) {
810: /* Now identify the consecutive vals belonging to the same row */
811: for (j=i,rstart=row[j]; j<n; j++) {
812: if (row[j] != rstart) break;
813: }
814: if (j < n) ncols = j-i;
815: else ncols = n-i;
816: MatSetValuesBlocked_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,mat->insertmode);
817: i = j;
818: }
819: }
820: MatStashScatterEnd_Private(&mat->bstash);
822: baij->roworiented = r1;
823: a->roworiented = r2;
825: ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworinted */
826: }
828: MatAssemblyBegin(baij->A,mode);
829: MatAssemblyEnd(baij->A,mode);
831: /* determine if any processor has disassembled, if so we must
832: also disassemble ourselfs, in order that we may reassemble. */
833: /*
834: if nonzero structure of submatrix B cannot change then we know that
835: no processor disassembled thus we can skip this stuff
836: */
837: if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) {
838: MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
839: if (mat->was_assembled && !other_disassembled) {
840: MatDisAssemble_MPISBAIJ(mat);
841: }
842: }
844: if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
845: MatSetUpMultiply_MPISBAIJ(mat); /* setup Mvctx and sMvctx */
846: }
847: MatAssemblyBegin(baij->B,mode);
848: MatAssemblyEnd(baij->B,mode);
850: PetscFree2(baij->rowvalues,baij->rowindices);
852: baij->rowvalues = NULL;
854: /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
855: if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
856: PetscObjectState state = baij->A->nonzerostate + baij->B->nonzerostate;
857: MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));
858: }
859: return(0);
860: }
862: extern PetscErrorCode MatSetValues_MPIBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
863: #include <petscdraw.h>
864: static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
865: {
866: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
867: PetscErrorCode ierr;
868: PetscInt bs = mat->rmap->bs;
869: PetscMPIInt rank = baij->rank;
870: PetscBool iascii,isdraw;
871: PetscViewer sviewer;
872: PetscViewerFormat format;
875: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
876: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
877: if (iascii) {
878: PetscViewerGetFormat(viewer,&format);
879: if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
880: MatInfo info;
881: MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
882: MatGetInfo(mat,MAT_LOCAL,&info);
883: PetscViewerASCIIPushSynchronized(viewer);
884: 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);
885: MatGetInfo(baij->A,MAT_LOCAL,&info);
886: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
887: MatGetInfo(baij->B,MAT_LOCAL,&info);
888: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
889: PetscViewerFlush(viewer);
890: PetscViewerASCIIPopSynchronized(viewer);
891: PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
892: VecScatterView(baij->Mvctx,viewer);
893: return(0);
894: } else if (format == PETSC_VIEWER_ASCII_INFO) {
895: PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);
896: return(0);
897: } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
898: return(0);
899: }
900: }
902: if (isdraw) {
903: PetscDraw draw;
904: PetscBool isnull;
905: PetscViewerDrawGetDraw(viewer,0,&draw);
906: PetscDrawIsNull(draw,&isnull);
907: if (isnull) return(0);
908: }
910: {
911: /* assemble the entire matrix onto first processor. */
912: Mat A;
913: Mat_SeqSBAIJ *Aloc;
914: Mat_SeqBAIJ *Bloc;
915: PetscInt M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs;
916: MatScalar *a;
917: const char *matname;
919: /* Should this be the same type as mat? */
920: MatCreate(PetscObjectComm((PetscObject)mat),&A);
921: if (!rank) {
922: MatSetSizes(A,M,N,M,N);
923: } else {
924: MatSetSizes(A,0,0,M,N);
925: }
926: MatSetType(A,MATMPISBAIJ);
927: MatMPISBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);
928: MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);
929: PetscLogObjectParent((PetscObject)mat,(PetscObject)A);
931: /* copy over the A part */
932: Aloc = (Mat_SeqSBAIJ*)baij->A->data;
933: ai = Aloc->i; aj = Aloc->j; a = Aloc->a;
934: PetscMalloc1(bs,&rvals);
936: for (i=0; i<mbs; i++) {
937: rvals[0] = bs*(baij->rstartbs + i);
938: for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
939: for (j=ai[i]; j<ai[i+1]; j++) {
940: col = (baij->cstartbs+aj[j])*bs;
941: for (k=0; k<bs; k++) {
942: MatSetValues_MPISBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
943: col++;
944: a += bs;
945: }
946: }
947: }
948: /* copy over the B part */
949: Bloc = (Mat_SeqBAIJ*)baij->B->data;
950: ai = Bloc->i; aj = Bloc->j; a = Bloc->a;
951: for (i=0; i<mbs; i++) {
953: rvals[0] = bs*(baij->rstartbs + i);
954: for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
955: for (j=ai[i]; j<ai[i+1]; j++) {
956: col = baij->garray[aj[j]]*bs;
957: for (k=0; k<bs; k++) {
958: MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
959: col++;
960: a += bs;
961: }
962: }
963: }
964: PetscFree(rvals);
965: MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
966: MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
967: /*
968: Everyone has to call to draw the matrix since the graphics waits are
969: synchronized across all processors that share the PetscDraw object
970: */
971: PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
972: PetscObjectGetName((PetscObject)mat,&matname);
973: if (!rank) {
974: PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,matname);
975: MatView_SeqSBAIJ(((Mat_MPISBAIJ*)(A->data))->A,sviewer);
976: }
977: PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
978: PetscViewerFlush(viewer);
979: MatDestroy(&A);
980: }
981: return(0);
982: }
984: /* Used for both MPIBAIJ and MPISBAIJ matrices */
985: #define MatView_MPISBAIJ_Binary MatView_MPIBAIJ_Binary
987: PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer)
988: {
990: PetscBool iascii,isdraw,issocket,isbinary;
993: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
994: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
995: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
996: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
997: if (iascii || isdraw || issocket) {
998: MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);
999: } else if (isbinary) {
1000: MatView_MPISBAIJ_Binary(mat,viewer);
1001: }
1002: return(0);
1003: }
1005: PetscErrorCode MatDestroy_MPISBAIJ(Mat mat)
1006: {
1007: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
1011: #if defined(PETSC_USE_LOG)
1012: PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N);
1013: #endif
1014: MatStashDestroy_Private(&mat->stash);
1015: MatStashDestroy_Private(&mat->bstash);
1016: MatDestroy(&baij->A);
1017: MatDestroy(&baij->B);
1018: #if defined(PETSC_USE_CTABLE)
1019: PetscTableDestroy(&baij->colmap);
1020: #else
1021: PetscFree(baij->colmap);
1022: #endif
1023: PetscFree(baij->garray);
1024: VecDestroy(&baij->lvec);
1025: VecScatterDestroy(&baij->Mvctx);
1026: VecDestroy(&baij->slvec0);
1027: VecDestroy(&baij->slvec0b);
1028: VecDestroy(&baij->slvec1);
1029: VecDestroy(&baij->slvec1a);
1030: VecDestroy(&baij->slvec1b);
1031: VecScatterDestroy(&baij->sMvctx);
1032: PetscFree2(baij->rowvalues,baij->rowindices);
1033: PetscFree(baij->barray);
1034: PetscFree(baij->hd);
1035: VecDestroy(&baij->diag);
1036: VecDestroy(&baij->bb1);
1037: VecDestroy(&baij->xx1);
1038: #if defined(PETSC_USE_REAL_MAT_SINGLE)
1039: PetscFree(baij->setvaluescopy);
1040: #endif
1041: PetscFree(baij->in_loc);
1042: PetscFree(baij->v_loc);
1043: PetscFree(baij->rangebs);
1044: PetscFree(mat->data);
1046: PetscObjectChangeTypeName((PetscObject)mat,NULL);
1047: PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
1048: PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
1049: PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C",NULL);
1050: PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocationCSR_C",NULL);
1051: #if defined(PETSC_HAVE_ELEMENTAL)
1052: PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_elemental_C",NULL);
1053: #endif
1054: #if defined(PETSC_HAVE_SCALAPACK)
1055: PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_scalapack_C",NULL);
1056: #endif
1057: PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_mpiaij_C",NULL);
1058: PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_mpibaij_C",NULL);
1059: return(0);
1060: }
1062: PetscErrorCode MatMult_MPISBAIJ_Hermitian(Mat A,Vec xx,Vec yy)
1063: {
1064: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1065: PetscErrorCode ierr;
1066: PetscInt mbs=a->mbs,bs=A->rmap->bs;
1067: PetscScalar *from;
1068: const PetscScalar *x;
1071: /* diagonal part */
1072: (*a->A->ops->mult)(a->A,xx,a->slvec1a);
1073: VecSet(a->slvec1b,0.0);
1075: /* subdiagonal part */
1076: if (!a->B->ops->multhermitiantranspose) SETERRQ1(PetscObjectComm((PetscObject)a->B),PETSC_ERR_SUP,"Not for type %s\n",((PetscObject)a->B)->type_name);
1077: (*a->B->ops->multhermitiantranspose)(a->B,xx,a->slvec0b);
1079: /* copy x into the vec slvec0 */
1080: VecGetArray(a->slvec0,&from);
1081: VecGetArrayRead(xx,&x);
1083: PetscArraycpy(from,x,bs*mbs);
1084: VecRestoreArray(a->slvec0,&from);
1085: VecRestoreArrayRead(xx,&x);
1087: VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1088: VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1089: /* supperdiagonal part */
1090: (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);
1091: return(0);
1092: }
1094: PetscErrorCode MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy)
1095: {
1096: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1097: PetscErrorCode ierr;
1098: PetscInt mbs=a->mbs,bs=A->rmap->bs;
1099: PetscScalar *from;
1100: const PetscScalar *x;
1103: /* diagonal part */
1104: (*a->A->ops->mult)(a->A,xx,a->slvec1a);
1105: VecSet(a->slvec1b,0.0);
1107: /* subdiagonal part */
1108: (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);
1110: /* copy x into the vec slvec0 */
1111: VecGetArray(a->slvec0,&from);
1112: VecGetArrayRead(xx,&x);
1114: PetscArraycpy(from,x,bs*mbs);
1115: VecRestoreArray(a->slvec0,&from);
1116: VecRestoreArrayRead(xx,&x);
1118: VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1119: VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1120: /* supperdiagonal part */
1121: (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);
1122: return(0);
1123: }
1125: PetscErrorCode MatMultAdd_MPISBAIJ_Hermitian(Mat A,Vec xx,Vec yy,Vec zz)
1126: {
1127: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1128: PetscErrorCode ierr;
1129: PetscInt mbs=a->mbs,bs=A->rmap->bs;
1130: PetscScalar *from,zero=0.0;
1131: const PetscScalar *x;
1134: /* diagonal part */
1135: (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);
1136: VecSet(a->slvec1b,zero);
1138: /* subdiagonal part */
1139: if (!a->B->ops->multhermitiantranspose) SETERRQ1(PetscObjectComm((PetscObject)a->B),PETSC_ERR_SUP,"Not for type %s\n",((PetscObject)a->B)->type_name);
1140: (*a->B->ops->multhermitiantranspose)(a->B,xx,a->slvec0b);
1142: /* copy x into the vec slvec0 */
1143: VecGetArray(a->slvec0,&from);
1144: VecGetArrayRead(xx,&x);
1145: PetscArraycpy(from,x,bs*mbs);
1146: VecRestoreArray(a->slvec0,&from);
1148: VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1149: VecRestoreArrayRead(xx,&x);
1150: VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1152: /* supperdiagonal part */
1153: (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);
1154: return(0);
1155: }
1157: PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1158: {
1159: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1160: PetscErrorCode ierr;
1161: PetscInt mbs=a->mbs,bs=A->rmap->bs;
1162: PetscScalar *from,zero=0.0;
1163: const PetscScalar *x;
1166: /* diagonal part */
1167: (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);
1168: VecSet(a->slvec1b,zero);
1170: /* subdiagonal part */
1171: (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);
1173: /* copy x into the vec slvec0 */
1174: VecGetArray(a->slvec0,&from);
1175: VecGetArrayRead(xx,&x);
1176: PetscArraycpy(from,x,bs*mbs);
1177: VecRestoreArray(a->slvec0,&from);
1179: VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1180: VecRestoreArrayRead(xx,&x);
1181: VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
1183: /* supperdiagonal part */
1184: (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);
1185: return(0);
1186: }
1188: /*
1189: This only works correctly for square matrices where the subblock A->A is the
1190: diagonal block
1191: */
1192: PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v)
1193: {
1194: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1198: /* if (a->rmap->N != a->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */
1199: MatGetDiagonal(a->A,v);
1200: return(0);
1201: }
1203: PetscErrorCode MatScale_MPISBAIJ(Mat A,PetscScalar aa)
1204: {
1205: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1209: MatScale(a->A,aa);
1210: MatScale(a->B,aa);
1211: return(0);
1212: }
1214: PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1215: {
1216: Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data;
1217: PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p;
1219: PetscInt bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB;
1220: PetscInt nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend;
1221: PetscInt *cmap,*idx_p,cstart = mat->rstartbs;
1224: if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active");
1225: mat->getrowactive = PETSC_TRUE;
1227: if (!mat->rowvalues && (idx || v)) {
1228: /*
1229: allocate enough space to hold information from the longest row.
1230: */
1231: Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data;
1232: Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ*)mat->B->data;
1233: PetscInt max = 1,mbs = mat->mbs,tmp;
1234: for (i=0; i<mbs; i++) {
1235: tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */
1236: if (max < tmp) max = tmp;
1237: }
1238: PetscMalloc2(max*bs2,&mat->rowvalues,max*bs2,&mat->rowindices);
1239: }
1241: if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows");
1242: lrow = row - brstart; /* local row index */
1244: pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
1245: if (!v) {pvA = NULL; pvB = NULL;}
1246: if (!idx) {pcA = NULL; if (!v) pcB = NULL;}
1247: (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
1248: (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
1249: nztot = nzA + nzB;
1251: cmap = mat->garray;
1252: if (v || idx) {
1253: if (nztot) {
1254: /* Sort by increasing column numbers, assuming A and B already sorted */
1255: PetscInt imark = -1;
1256: if (v) {
1257: *v = v_p = mat->rowvalues;
1258: for (i=0; i<nzB; i++) {
1259: if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i];
1260: else break;
1261: }
1262: imark = i;
1263: for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i];
1264: for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i];
1265: }
1266: if (idx) {
1267: *idx = idx_p = mat->rowindices;
1268: if (imark > -1) {
1269: for (i=0; i<imark; i++) {
1270: idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1271: }
1272: } else {
1273: for (i=0; i<nzB; i++) {
1274: if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1275: else break;
1276: }
1277: imark = i;
1278: }
1279: for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i];
1280: for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ;
1281: }
1282: } else {
1283: if (idx) *idx = NULL;
1284: if (v) *v = NULL;
1285: }
1286: }
1287: *nz = nztot;
1288: (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
1289: (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
1290: return(0);
1291: }
1293: PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1294: {
1295: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
1298: if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first");
1299: baij->getrowactive = PETSC_FALSE;
1300: return(0);
1301: }
1303: PetscErrorCode MatGetRowUpperTriangular_MPISBAIJ(Mat A)
1304: {
1305: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1306: Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;
1309: aA->getrow_utriangular = PETSC_TRUE;
1310: return(0);
1311: }
1312: PetscErrorCode MatRestoreRowUpperTriangular_MPISBAIJ(Mat A)
1313: {
1314: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1315: Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;
1318: aA->getrow_utriangular = PETSC_FALSE;
1319: return(0);
1320: }
1322: PetscErrorCode MatRealPart_MPISBAIJ(Mat A)
1323: {
1324: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1328: MatRealPart(a->A);
1329: MatRealPart(a->B);
1330: return(0);
1331: }
1333: PetscErrorCode MatImaginaryPart_MPISBAIJ(Mat A)
1334: {
1335: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1339: MatImaginaryPart(a->A);
1340: MatImaginaryPart(a->B);
1341: return(0);
1342: }
1344: /* Check if isrow is a subset of iscol_local, called by MatCreateSubMatrix_MPISBAIJ()
1345: Input: isrow - distributed(parallel),
1346: iscol_local - locally owned (seq)
1347: */
1348: PetscErrorCode ISEqual_private(IS isrow,IS iscol_local,PetscBool *flg)
1349: {
1351: PetscInt sz1,sz2,*a1,*a2,i,j,k,nmatch;
1352: const PetscInt *ptr1,*ptr2;
1355: ISGetLocalSize(isrow,&sz1);
1356: ISGetLocalSize(iscol_local,&sz2);
1357: if (sz1 > sz2) {
1358: *flg = PETSC_FALSE;
1359: return(0);
1360: }
1362: ISGetIndices(isrow,&ptr1);
1363: ISGetIndices(iscol_local,&ptr2);
1365: PetscMalloc1(sz1,&a1);
1366: PetscMalloc1(sz2,&a2);
1367: PetscArraycpy(a1,ptr1,sz1);
1368: PetscArraycpy(a2,ptr2,sz2);
1369: PetscSortInt(sz1,a1);
1370: PetscSortInt(sz2,a2);
1372: nmatch=0;
1373: k = 0;
1374: for (i=0; i<sz1; i++){
1375: for (j=k; j<sz2; j++){
1376: if (a1[i] == a2[j]) {
1377: k = j; nmatch++;
1378: break;
1379: }
1380: }
1381: }
1382: ISRestoreIndices(isrow,&ptr1);
1383: ISRestoreIndices(iscol_local,&ptr2);
1384: PetscFree(a1);
1385: PetscFree(a2);
1386: if (nmatch < sz1) {
1387: *flg = PETSC_FALSE;
1388: } else {
1389: *flg = PETSC_TRUE;
1390: }
1391: return(0);
1392: }
1394: PetscErrorCode MatCreateSubMatrix_MPISBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
1395: {
1397: IS iscol_local;
1398: PetscInt csize;
1399: PetscBool isequal;
1402: ISGetLocalSize(iscol,&csize);
1403: if (call == MAT_REUSE_MATRIX) {
1404: PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);
1405: if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
1406: } else {
1407: ISAllGather(iscol,&iscol_local);
1408: ISEqual_private(isrow,iscol_local,&isequal);
1409: if (!isequal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"For symmetric format, iscol must equal isrow");
1410: }
1412: /* now call MatCreateSubMatrix_MPIBAIJ() */
1413: MatCreateSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);
1414: if (call == MAT_INITIAL_MATRIX) {
1415: PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);
1416: ISDestroy(&iscol_local);
1417: }
1418: return(0);
1419: }
1421: PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A)
1422: {
1423: Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data;
1427: MatZeroEntries(l->A);
1428: MatZeroEntries(l->B);
1429: return(0);
1430: }
1432: PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info)
1433: {
1434: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)matin->data;
1435: Mat A = a->A,B = a->B;
1437: PetscLogDouble isend[5],irecv[5];
1440: info->block_size = (PetscReal)matin->rmap->bs;
1442: MatGetInfo(A,MAT_LOCAL,info);
1444: isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
1445: isend[3] = info->memory; isend[4] = info->mallocs;
1447: MatGetInfo(B,MAT_LOCAL,info);
1449: isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
1450: isend[3] += info->memory; isend[4] += info->mallocs;
1451: if (flag == MAT_LOCAL) {
1452: info->nz_used = isend[0];
1453: info->nz_allocated = isend[1];
1454: info->nz_unneeded = isend[2];
1455: info->memory = isend[3];
1456: info->mallocs = isend[4];
1457: } else if (flag == MAT_GLOBAL_MAX) {
1458: MPIU_Allreduce(isend,irecv,5,MPIU_PETSCLOGDOUBLE,MPI_MAX,PetscObjectComm((PetscObject)matin));
1460: info->nz_used = irecv[0];
1461: info->nz_allocated = irecv[1];
1462: info->nz_unneeded = irecv[2];
1463: info->memory = irecv[3];
1464: info->mallocs = irecv[4];
1465: } else if (flag == MAT_GLOBAL_SUM) {
1466: MPIU_Allreduce(isend,irecv,5,MPIU_PETSCLOGDOUBLE,MPI_SUM,PetscObjectComm((PetscObject)matin));
1468: info->nz_used = irecv[0];
1469: info->nz_allocated = irecv[1];
1470: info->nz_unneeded = irecv[2];
1471: info->memory = irecv[3];
1472: info->mallocs = irecv[4];
1473: } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag);
1474: info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */
1475: info->fill_ratio_needed = 0;
1476: info->factor_mallocs = 0;
1477: return(0);
1478: }
1480: PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op,PetscBool flg)
1481: {
1482: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1483: Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;
1487: switch (op) {
1488: case MAT_NEW_NONZERO_LOCATIONS:
1489: case MAT_NEW_NONZERO_ALLOCATION_ERR:
1490: case MAT_UNUSED_NONZERO_LOCATION_ERR:
1491: case MAT_KEEP_NONZERO_PATTERN:
1492: case MAT_SUBMAT_SINGLEIS:
1493: case MAT_NEW_NONZERO_LOCATION_ERR:
1494: MatCheckPreallocated(A,1);
1495: MatSetOption(a->A,op,flg);
1496: MatSetOption(a->B,op,flg);
1497: break;
1498: case MAT_ROW_ORIENTED:
1499: MatCheckPreallocated(A,1);
1500: a->roworiented = flg;
1502: MatSetOption(a->A,op,flg);
1503: MatSetOption(a->B,op,flg);
1504: break;
1505: case MAT_NEW_DIAGONALS:
1506: case MAT_SORTED_FULL:
1507: PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1508: break;
1509: case MAT_IGNORE_OFF_PROC_ENTRIES:
1510: a->donotstash = flg;
1511: break;
1512: case MAT_USE_HASH_TABLE:
1513: a->ht_flag = flg;
1514: break;
1515: case MAT_HERMITIAN:
1516: MatCheckPreallocated(A,1);
1517: MatSetOption(a->A,op,flg);
1518: #if defined(PETSC_USE_COMPLEX)
1519: if (flg) { /* need different mat-vec ops */
1520: A->ops->mult = MatMult_MPISBAIJ_Hermitian;
1521: A->ops->multadd = MatMultAdd_MPISBAIJ_Hermitian;
1522: A->ops->multtranspose = NULL;
1523: A->ops->multtransposeadd = NULL;
1524: A->symmetric = PETSC_FALSE;
1525: }
1526: #endif
1527: break;
1528: case MAT_SPD:
1529: case MAT_SYMMETRIC:
1530: MatCheckPreallocated(A,1);
1531: MatSetOption(a->A,op,flg);
1532: #if defined(PETSC_USE_COMPLEX)
1533: if (flg) { /* restore to use default mat-vec ops */
1534: A->ops->mult = MatMult_MPISBAIJ;
1535: A->ops->multadd = MatMultAdd_MPISBAIJ;
1536: A->ops->multtranspose = MatMult_MPISBAIJ;
1537: A->ops->multtransposeadd = MatMultAdd_MPISBAIJ;
1538: }
1539: #endif
1540: break;
1541: case MAT_STRUCTURALLY_SYMMETRIC:
1542: MatCheckPreallocated(A,1);
1543: MatSetOption(a->A,op,flg);
1544: break;
1545: case MAT_SYMMETRY_ETERNAL:
1546: if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix must be symmetric");
1547: PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1548: break;
1549: case MAT_IGNORE_LOWER_TRIANGULAR:
1550: aA->ignore_ltriangular = flg;
1551: break;
1552: case MAT_ERROR_LOWER_TRIANGULAR:
1553: aA->ignore_ltriangular = flg;
1554: break;
1555: case MAT_GETROW_UPPERTRIANGULAR:
1556: aA->getrow_utriangular = flg;
1557: break;
1558: default:
1559: SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
1560: }
1561: return(0);
1562: }
1564: PetscErrorCode MatTranspose_MPISBAIJ(Mat A,MatReuse reuse,Mat *B)
1565: {
1569: if (reuse == MAT_INITIAL_MATRIX) {
1570: MatDuplicate(A,MAT_COPY_VALUES,B);
1571: } else if (reuse == MAT_REUSE_MATRIX) {
1572: MatCopy(A,*B,SAME_NONZERO_PATTERN);
1573: }
1574: return(0);
1575: }
1577: PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr)
1578: {
1579: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
1580: Mat a = baij->A, b=baij->B;
1582: PetscInt nv,m,n;
1583: PetscBool flg;
1586: if (ll != rr) {
1587: VecEqual(ll,rr,&flg);
1588: if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n");
1589: }
1590: if (!ll) return(0);
1592: MatGetLocalSize(mat,&m,&n);
1593: if (m != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"For symmetric format, local size %d %d must be same",m,n);
1595: VecGetLocalSize(rr,&nv);
1596: if (nv!=n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left and right vector non-conforming local size");
1598: VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);
1600: /* left diagonalscale the off-diagonal part */
1601: (*b->ops->diagonalscale)(b,ll,NULL);
1603: /* scale the diagonal part */
1604: (*a->ops->diagonalscale)(a,ll,rr);
1606: /* right diagonalscale the off-diagonal part */
1607: VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);
1608: (*b->ops->diagonalscale)(b,NULL,baij->lvec);
1609: return(0);
1610: }
1612: PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A)
1613: {
1614: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1618: MatSetUnfactored(a->A);
1619: return(0);
1620: }
1622: static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat*);
1624: PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscBool *flag)
1625: {
1626: Mat_MPISBAIJ *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data;
1627: Mat a,b,c,d;
1628: PetscBool flg;
1632: a = matA->A; b = matA->B;
1633: c = matB->A; d = matB->B;
1635: MatEqual(a,c,&flg);
1636: if (flg) {
1637: MatEqual(b,d,&flg);
1638: }
1639: MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
1640: return(0);
1641: }
1643: PetscErrorCode MatCopy_MPISBAIJ(Mat A,Mat B,MatStructure str)
1644: {
1646: PetscBool isbaij;
1649: PetscObjectTypeCompareAny((PetscObject)B,&isbaij,MATSEQSBAIJ,MATMPISBAIJ,"");
1650: if (!isbaij) SETERRQ1(PetscObjectComm((PetscObject)B),PETSC_ERR_SUP,"Not for matrix type %s",((PetscObject)B)->type_name);
1651: /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
1652: if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
1653: MatGetRowUpperTriangular(A);
1654: MatCopy_Basic(A,B,str);
1655: MatRestoreRowUpperTriangular(A);
1656: } else {
1657: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1658: Mat_MPISBAIJ *b = (Mat_MPISBAIJ*)B->data;
1660: MatCopy(a->A,b->A,str);
1661: MatCopy(a->B,b->B,str);
1662: }
1663: PetscObjectStateIncrease((PetscObject)B);
1664: return(0);
1665: }
1667: PetscErrorCode MatSetUp_MPISBAIJ(Mat A)
1668: {
1672: MatMPISBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,NULL,PETSC_DEFAULT,NULL);
1673: return(0);
1674: }
1676: PetscErrorCode MatAXPY_MPISBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
1677: {
1679: Mat_MPISBAIJ *xx=(Mat_MPISBAIJ*)X->data,*yy=(Mat_MPISBAIJ*)Y->data;
1680: PetscBLASInt bnz,one=1;
1681: Mat_SeqSBAIJ *xa,*ya;
1682: Mat_SeqBAIJ *xb,*yb;
1685: if (str == SAME_NONZERO_PATTERN) {
1686: PetscScalar alpha = a;
1687: xa = (Mat_SeqSBAIJ*)xx->A->data;
1688: ya = (Mat_SeqSBAIJ*)yy->A->data;
1689: PetscBLASIntCast(xa->nz,&bnz);
1690: PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xa->a,&one,ya->a,&one));
1691: xb = (Mat_SeqBAIJ*)xx->B->data;
1692: yb = (Mat_SeqBAIJ*)yy->B->data;
1693: PetscBLASIntCast(xb->nz,&bnz);
1694: PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xb->a,&one,yb->a,&one));
1695: PetscObjectStateIncrease((PetscObject)Y);
1696: } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
1697: MatSetOption(X,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
1698: MatAXPY_Basic(Y,a,X,str);
1699: MatSetOption(X,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
1700: } else {
1701: Mat B;
1702: PetscInt *nnz_d,*nnz_o,bs=Y->rmap->bs;
1703: if (bs != X->rmap->bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrices must have same block size");
1704: MatGetRowUpperTriangular(X);
1705: MatGetRowUpperTriangular(Y);
1706: PetscMalloc1(yy->A->rmap->N,&nnz_d);
1707: PetscMalloc1(yy->B->rmap->N,&nnz_o);
1708: MatCreate(PetscObjectComm((PetscObject)Y),&B);
1709: PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
1710: MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
1711: MatSetBlockSizesFromMats(B,Y,Y);
1712: MatSetType(B,MATMPISBAIJ);
1713: MatAXPYGetPreallocation_SeqSBAIJ(yy->A,xx->A,nnz_d);
1714: MatAXPYGetPreallocation_MPIBAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);
1715: MatMPISBAIJSetPreallocation(B,bs,0,nnz_d,0,nnz_o);
1716: MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
1717: MatHeaderReplace(Y,&B);
1718: PetscFree(nnz_d);
1719: PetscFree(nnz_o);
1720: MatRestoreRowUpperTriangular(X);
1721: MatRestoreRowUpperTriangular(Y);
1722: }
1723: return(0);
1724: }
1726: PetscErrorCode MatCreateSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[])
1727: {
1729: PetscInt i;
1730: PetscBool flg;
1733: MatCreateSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B); /* B[] are sbaij matrices */
1734: for (i=0; i<n; i++) {
1735: ISEqual(irow[i],icol[i],&flg);
1736: if (!flg) {
1737: MatSeqSBAIJZeroOps_Private(*B[i]);
1738: }
1739: }
1740: return(0);
1741: }
1743: PetscErrorCode MatShift_MPISBAIJ(Mat Y,PetscScalar a)
1744: {
1746: Mat_MPISBAIJ *maij = (Mat_MPISBAIJ*)Y->data;
1747: Mat_SeqSBAIJ *aij = (Mat_SeqSBAIJ*)maij->A->data;
1750: if (!Y->preallocated) {
1751: MatMPISBAIJSetPreallocation(Y,Y->rmap->bs,1,NULL,0,NULL);
1752: } else if (!aij->nz) {
1753: PetscInt nonew = aij->nonew;
1754: MatSeqSBAIJSetPreallocation(maij->A,Y->rmap->bs,1,NULL);
1755: aij->nonew = nonew;
1756: }
1757: MatShift_Basic(Y,a);
1758: return(0);
1759: }
1761: PetscErrorCode MatMissingDiagonal_MPISBAIJ(Mat A,PetscBool *missing,PetscInt *d)
1762: {
1763: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1767: if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices");
1768: MatMissingDiagonal(a->A,missing,d);
1769: if (d) {
1770: PetscInt rstart;
1771: MatGetOwnershipRange(A,&rstart,NULL);
1772: *d += rstart/A->rmap->bs;
1774: }
1775: return(0);
1776: }
1778: PetscErrorCode MatGetDiagonalBlock_MPISBAIJ(Mat A,Mat *a)
1779: {
1781: *a = ((Mat_MPISBAIJ*)A->data)->A;
1782: return(0);
1783: }
1785: /* -------------------------------------------------------------------*/
1786: static struct _MatOps MatOps_Values = {MatSetValues_MPISBAIJ,
1787: MatGetRow_MPISBAIJ,
1788: MatRestoreRow_MPISBAIJ,
1789: MatMult_MPISBAIJ,
1790: /* 4*/ MatMultAdd_MPISBAIJ,
1791: MatMult_MPISBAIJ, /* transpose versions are same as non-transpose */
1792: MatMultAdd_MPISBAIJ,
1793: NULL,
1794: NULL,
1795: NULL,
1796: /* 10*/ NULL,
1797: NULL,
1798: NULL,
1799: MatSOR_MPISBAIJ,
1800: MatTranspose_MPISBAIJ,
1801: /* 15*/ MatGetInfo_MPISBAIJ,
1802: MatEqual_MPISBAIJ,
1803: MatGetDiagonal_MPISBAIJ,
1804: MatDiagonalScale_MPISBAIJ,
1805: MatNorm_MPISBAIJ,
1806: /* 20*/ MatAssemblyBegin_MPISBAIJ,
1807: MatAssemblyEnd_MPISBAIJ,
1808: MatSetOption_MPISBAIJ,
1809: MatZeroEntries_MPISBAIJ,
1810: /* 24*/ NULL,
1811: NULL,
1812: NULL,
1813: NULL,
1814: NULL,
1815: /* 29*/ MatSetUp_MPISBAIJ,
1816: NULL,
1817: NULL,
1818: MatGetDiagonalBlock_MPISBAIJ,
1819: NULL,
1820: /* 34*/ MatDuplicate_MPISBAIJ,
1821: NULL,
1822: NULL,
1823: NULL,
1824: NULL,
1825: /* 39*/ MatAXPY_MPISBAIJ,
1826: MatCreateSubMatrices_MPISBAIJ,
1827: MatIncreaseOverlap_MPISBAIJ,
1828: MatGetValues_MPISBAIJ,
1829: MatCopy_MPISBAIJ,
1830: /* 44*/ NULL,
1831: MatScale_MPISBAIJ,
1832: MatShift_MPISBAIJ,
1833: NULL,
1834: NULL,
1835: /* 49*/ NULL,
1836: NULL,
1837: NULL,
1838: NULL,
1839: NULL,
1840: /* 54*/ NULL,
1841: NULL,
1842: MatSetUnfactored_MPISBAIJ,
1843: NULL,
1844: MatSetValuesBlocked_MPISBAIJ,
1845: /* 59*/ MatCreateSubMatrix_MPISBAIJ,
1846: NULL,
1847: NULL,
1848: NULL,
1849: NULL,
1850: /* 64*/ NULL,
1851: NULL,
1852: NULL,
1853: NULL,
1854: NULL,
1855: /* 69*/ MatGetRowMaxAbs_MPISBAIJ,
1856: NULL,
1857: MatConvert_MPISBAIJ_Basic,
1858: NULL,
1859: NULL,
1860: /* 74*/ NULL,
1861: NULL,
1862: NULL,
1863: NULL,
1864: NULL,
1865: /* 79*/ NULL,
1866: NULL,
1867: NULL,
1868: NULL,
1869: MatLoad_MPISBAIJ,
1870: /* 84*/ NULL,
1871: NULL,
1872: NULL,
1873: NULL,
1874: NULL,
1875: /* 89*/ NULL,
1876: NULL,
1877: NULL,
1878: NULL,
1879: NULL,
1880: /* 94*/ NULL,
1881: NULL,
1882: NULL,
1883: NULL,
1884: NULL,
1885: /* 99*/ NULL,
1886: NULL,
1887: NULL,
1888: NULL,
1889: NULL,
1890: /*104*/ NULL,
1891: MatRealPart_MPISBAIJ,
1892: MatImaginaryPart_MPISBAIJ,
1893: MatGetRowUpperTriangular_MPISBAIJ,
1894: MatRestoreRowUpperTriangular_MPISBAIJ,
1895: /*109*/ NULL,
1896: NULL,
1897: NULL,
1898: NULL,
1899: MatMissingDiagonal_MPISBAIJ,
1900: /*114*/ NULL,
1901: NULL,
1902: NULL,
1903: NULL,
1904: NULL,
1905: /*119*/ NULL,
1906: NULL,
1907: NULL,
1908: NULL,
1909: NULL,
1910: /*124*/ NULL,
1911: NULL,
1912: NULL,
1913: NULL,
1914: NULL,
1915: /*129*/ NULL,
1916: NULL,
1917: NULL,
1918: NULL,
1919: NULL,
1920: /*134*/ NULL,
1921: NULL,
1922: NULL,
1923: NULL,
1924: NULL,
1925: /*139*/ MatSetBlockSizes_Default,
1926: NULL,
1927: NULL,
1928: NULL,
1929: NULL,
1930: /*144*/MatCreateMPIMatConcatenateSeqMat_MPISBAIJ
1931: };
1933: PetscErrorCode MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz)
1934: {
1935: Mat_MPISBAIJ *b = (Mat_MPISBAIJ*)B->data;
1937: PetscInt i,mbs,Mbs;
1938: PetscMPIInt size;
1941: MatSetBlockSize(B,PetscAbs(bs));
1942: PetscLayoutSetUp(B->rmap);
1943: PetscLayoutSetUp(B->cmap);
1944: PetscLayoutGetBlockSize(B->rmap,&bs);
1945: if (B->rmap->N > B->cmap->N) SETERRQ2(PetscObjectComm((PetscObject)B),PETSC_ERR_SUP,"MPISBAIJ matrix cannot have more rows %D than columns %D",B->rmap->N,B->cmap->N);
1946: if (B->rmap->n > B->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_SUP,"MPISBAIJ matrix cannot have more local rows %D than columns %D",B->rmap->n,B->cmap->n);
1948: mbs = B->rmap->n/bs;
1949: Mbs = B->rmap->N/bs;
1950: 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);
1952: B->rmap->bs = bs;
1953: b->bs2 = bs*bs;
1954: b->mbs = mbs;
1955: b->Mbs = Mbs;
1956: b->nbs = B->cmap->n/bs;
1957: b->Nbs = B->cmap->N/bs;
1959: for (i=0; i<=b->size; i++) {
1960: b->rangebs[i] = B->rmap->range[i]/bs;
1961: }
1962: b->rstartbs = B->rmap->rstart/bs;
1963: b->rendbs = B->rmap->rend/bs;
1965: b->cstartbs = B->cmap->rstart/bs;
1966: b->cendbs = B->cmap->rend/bs;
1968: #if defined(PETSC_USE_CTABLE)
1969: PetscTableDestroy(&b->colmap);
1970: #else
1971: PetscFree(b->colmap);
1972: #endif
1973: PetscFree(b->garray);
1974: VecDestroy(&b->lvec);
1975: VecScatterDestroy(&b->Mvctx);
1976: VecDestroy(&b->slvec0);
1977: VecDestroy(&b->slvec0b);
1978: VecDestroy(&b->slvec1);
1979: VecDestroy(&b->slvec1a);
1980: VecDestroy(&b->slvec1b);
1981: VecScatterDestroy(&b->sMvctx);
1983: /* Because the B will have been resized we simply destroy it and create a new one each time */
1984: MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);
1985: MatDestroy(&b->B);
1986: MatCreate(PETSC_COMM_SELF,&b->B);
1987: MatSetSizes(b->B,B->rmap->n,size > 1 ? B->cmap->N : 0,B->rmap->n,size > 1 ? B->cmap->N : 0);
1988: MatSetType(b->B,MATSEQBAIJ);
1989: PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);
1991: if (!B->preallocated) {
1992: MatCreate(PETSC_COMM_SELF,&b->A);
1993: MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
1994: MatSetType(b->A,MATSEQSBAIJ);
1995: PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);
1996: MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);
1997: }
1999: MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);
2000: MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);
2002: B->preallocated = PETSC_TRUE;
2003: B->was_assembled = PETSC_FALSE;
2004: B->assembled = PETSC_FALSE;
2005: return(0);
2006: }
2008: PetscErrorCode MatMPISBAIJSetPreallocationCSR_MPISBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[])
2009: {
2010: PetscInt m,rstart,cend;
2011: PetscInt i,j,d,nz,bd, nz_max=0,*d_nnz=NULL,*o_nnz=NULL;
2012: const PetscInt *JJ =NULL;
2013: PetscScalar *values=NULL;
2014: PetscBool roworiented = ((Mat_MPISBAIJ*)B->data)->roworiented;
2016: PetscBool nooffprocentries;
2019: if (bs < 1) SETERRQ1(PetscObjectComm((PetscObject)B),PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs);
2020: PetscLayoutSetBlockSize(B->rmap,bs);
2021: PetscLayoutSetBlockSize(B->cmap,bs);
2022: PetscLayoutSetUp(B->rmap);
2023: PetscLayoutSetUp(B->cmap);
2024: PetscLayoutGetBlockSize(B->rmap,&bs);
2025: m = B->rmap->n/bs;
2026: rstart = B->rmap->rstart/bs;
2027: cend = B->cmap->rend/bs;
2029: if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]);
2030: PetscMalloc2(m,&d_nnz,m,&o_nnz);
2031: for (i=0; i<m; i++) {
2032: nz = ii[i+1] - ii[i];
2033: if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz);
2034: /* count the ones on the diagonal and above, split into diagonal and off diagonal portions. */
2035: JJ = jj + ii[i];
2036: bd = 0;
2037: for (j=0; j<nz; j++) {
2038: if (*JJ >= i + rstart) break;
2039: JJ++;
2040: bd++;
2041: }
2042: d = 0;
2043: for (; j<nz; j++) {
2044: if (*JJ++ >= cend) break;
2045: d++;
2046: }
2047: d_nnz[i] = d;
2048: o_nnz[i] = nz - d - bd;
2049: nz = nz - bd;
2050: nz_max = PetscMax(nz_max,nz);
2051: }
2052: MatMPISBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);
2053: MatSetOption(B,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE);
2054: PetscFree2(d_nnz,o_nnz);
2056: values = (PetscScalar*)V;
2057: if (!values) {
2058: PetscCalloc1(bs*bs*nz_max,&values);
2059: }
2060: for (i=0; i<m; i++) {
2061: PetscInt row = i + rstart;
2062: PetscInt ncols = ii[i+1] - ii[i];
2063: const PetscInt *icols = jj + ii[i];
2064: if (bs == 1 || !roworiented) { /* block ordering matches the non-nested layout of MatSetValues so we can insert entire rows */
2065: const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0);
2066: MatSetValuesBlocked_MPISBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);
2067: } else { /* block ordering does not match so we can only insert one block at a time. */
2068: PetscInt j;
2069: for (j=0; j<ncols; j++) {
2070: const PetscScalar *svals = values + (V ? (bs*bs*(ii[i]+j)) : 0);
2071: MatSetValuesBlocked_MPISBAIJ(B,1,&row,1,&icols[j],svals,INSERT_VALUES);
2072: }
2073: }
2074: }
2076: if (!V) { PetscFree(values); }
2077: nooffprocentries = B->nooffprocentries;
2078: B->nooffprocentries = PETSC_TRUE;
2079: MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
2080: MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
2081: B->nooffprocentries = nooffprocentries;
2083: MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
2084: return(0);
2085: }
2087: /*MC
2088: MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices,
2089: based on block compressed sparse row format. Only the upper triangular portion of the "diagonal" portion of
2090: the matrix is stored.
2092: For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you
2093: can call MatSetOption(Mat, MAT_HERMITIAN);
2095: Options Database Keys:
2096: . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions()
2098: Notes:
2099: The number of rows in the matrix must be less than or equal to the number of columns. Similarly the number of rows in the
2100: diagonal portion of the matrix of each process has to less than or equal the number of columns.
2102: Level: beginner
2104: .seealso: MatCreateBAIJ(), MATSEQSBAIJ, MatType
2105: M*/
2107: PETSC_EXTERN PetscErrorCode MatCreate_MPISBAIJ(Mat B)
2108: {
2109: Mat_MPISBAIJ *b;
2111: PetscBool flg = PETSC_FALSE;
2114: PetscNewLog(B,&b);
2115: B->data = (void*)b;
2116: PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
2118: B->ops->destroy = MatDestroy_MPISBAIJ;
2119: B->ops->view = MatView_MPISBAIJ;
2120: B->assembled = PETSC_FALSE;
2121: B->insertmode = NOT_SET_VALUES;
2123: MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);
2124: MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);
2126: /* build local table of row and column ownerships */
2127: PetscMalloc1(b->size+2,&b->rangebs);
2129: /* build cache for off array entries formed */
2130: MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);
2132: b->donotstash = PETSC_FALSE;
2133: b->colmap = NULL;
2134: b->garray = NULL;
2135: b->roworiented = PETSC_TRUE;
2137: /* stuff used in block assembly */
2138: b->barray = NULL;
2140: /* stuff used for matrix vector multiply */
2141: b->lvec = NULL;
2142: b->Mvctx = NULL;
2143: b->slvec0 = NULL;
2144: b->slvec0b = NULL;
2145: b->slvec1 = NULL;
2146: b->slvec1a = NULL;
2147: b->slvec1b = NULL;
2148: b->sMvctx = NULL;
2150: /* stuff for MatGetRow() */
2151: b->rowindices = NULL;
2152: b->rowvalues = NULL;
2153: b->getrowactive = PETSC_FALSE;
2155: /* hash table stuff */
2156: b->ht = NULL;
2157: b->hd = NULL;
2158: b->ht_size = 0;
2159: b->ht_flag = PETSC_FALSE;
2160: b->ht_fact = 0;
2161: b->ht_total_ct = 0;
2162: b->ht_insert_ct = 0;
2164: /* stuff for MatCreateSubMatrices_MPIBAIJ_local() */
2165: b->ijonly = PETSC_FALSE;
2167: b->in_loc = NULL;
2168: b->v_loc = NULL;
2169: b->n_loc = 0;
2171: PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPISBAIJ);
2172: PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPISBAIJ);
2173: PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",MatMPISBAIJSetPreallocation_MPISBAIJ);
2174: PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocationCSR_C",MatMPISBAIJSetPreallocationCSR_MPISBAIJ);
2175: #if defined(PETSC_HAVE_ELEMENTAL)
2176: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_elemental_C",MatConvert_MPISBAIJ_Elemental);
2177: #endif
2178: #if defined(PETSC_HAVE_SCALAPACK)
2179: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_scalapack_C",MatConvert_SBAIJ_ScaLAPACK);
2180: #endif
2181: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_mpiaij_C",MatConvert_MPISBAIJ_Basic);
2182: PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_mpibaij_C",MatConvert_MPISBAIJ_Basic);
2184: B->symmetric = PETSC_TRUE;
2185: B->structurally_symmetric = PETSC_TRUE;
2186: B->symmetric_set = PETSC_TRUE;
2187: B->structurally_symmetric_set = PETSC_TRUE;
2188: B->symmetric_eternal = PETSC_TRUE;
2189: #if defined(PETSC_USE_COMPLEX)
2190: B->hermitian = PETSC_FALSE;
2191: B->hermitian_set = PETSC_FALSE;
2192: #else
2193: B->hermitian = PETSC_TRUE;
2194: B->hermitian_set = PETSC_TRUE;
2195: #endif
2197: PetscObjectChangeTypeName((PetscObject)B,MATMPISBAIJ);
2198: PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPISBAIJ matrix 1","Mat");
2199: PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",flg,&flg,NULL);
2200: if (flg) {
2201: PetscReal fact = 1.39;
2202: MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);
2203: PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);
2204: if (fact <= 1.0) fact = 1.39;
2205: MatMPIBAIJSetHashTableFactor(B,fact);
2206: PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);
2207: }
2208: PetscOptionsEnd();
2209: return(0);
2210: }
2212: /*MC
2213: MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices.
2215: This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator,
2216: and MATMPISBAIJ otherwise.
2218: Options Database Keys:
2219: . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions()
2221: Level: beginner
2223: .seealso: MatCreateMPISBAIJ, MATSEQSBAIJ, MATMPISBAIJ
2224: M*/
2226: /*@C
2227: MatMPISBAIJSetPreallocation - For good matrix assembly performance
2228: the user should preallocate the matrix storage by setting the parameters
2229: d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately,
2230: performance can be increased by more than a factor of 50.
2232: Collective on Mat
2234: Input Parameters:
2235: + B - the matrix
2236: . bs - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
2237: blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
2238: . d_nz - number of block nonzeros per block row in diagonal portion of local
2239: submatrix (same for all local rows)
2240: . d_nnz - array containing the number of block nonzeros in the various block rows
2241: in the upper triangular and diagonal part of the in diagonal portion of the local
2242: (possibly different for each block row) or NULL. If you plan to factor the matrix you must leave room
2243: for the diagonal entry and set a value even if it is zero.
2244: . o_nz - number of block nonzeros per block row in the off-diagonal portion of local
2245: submatrix (same for all local rows).
2246: - o_nnz - array containing the number of nonzeros in the various block rows of the
2247: off-diagonal portion of the local submatrix that is right of the diagonal
2248: (possibly different for each block row) or NULL.
2251: Options Database Keys:
2252: + -mat_no_unroll - uses code that does not unroll the loops in the
2253: block calculations (much slower)
2254: - -mat_block_size - size of the blocks to use
2256: Notes:
2258: If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor
2259: than it must be used on all processors that share the object for that argument.
2261: If the *_nnz parameter is given then the *_nz parameter is ignored
2263: Storage Information:
2264: For a square global matrix we define each processor's diagonal portion
2265: to be its local rows and the corresponding columns (a square submatrix);
2266: each processor's off-diagonal portion encompasses the remainder of the
2267: local matrix (a rectangular submatrix).
2269: The user can specify preallocated storage for the diagonal part of
2270: the local submatrix with either d_nz or d_nnz (not both). Set
2271: d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
2272: memory allocation. Likewise, specify preallocated storage for the
2273: off-diagonal part of the local submatrix with o_nz or o_nnz (not both).
2275: You can call MatGetInfo() to get information on how effective the preallocation was;
2276: for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
2277: You can also run with the option -info and look for messages with the string
2278: malloc in them to see if additional memory allocation was needed.
2280: Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
2281: the figure below we depict these three local rows and all columns (0-11).
2283: .vb
2284: 0 1 2 3 4 5 6 7 8 9 10 11
2285: --------------------------
2286: row 3 |. . . d d d o o o o o o
2287: row 4 |. . . d d d o o o o o o
2288: row 5 |. . . d d d o o o o o o
2289: --------------------------
2290: .ve
2292: Thus, any entries in the d locations are stored in the d (diagonal)
2293: submatrix, and any entries in the o locations are stored in the
2294: o (off-diagonal) submatrix. Note that the d matrix is stored in
2295: MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format.
2297: Now d_nz should indicate the number of block nonzeros per row in the upper triangular
2298: plus the diagonal part of the d matrix,
2299: and o_nz should indicate the number of block nonzeros per row in the o matrix
2301: In general, for PDE problems in which most nonzeros are near the diagonal,
2302: one expects d_nz >> o_nz. For large problems you MUST preallocate memory
2303: or you will get TERRIBLE performance; see the users' manual chapter on
2304: matrices.
2306: Level: intermediate
2308: .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ(), PetscSplitOwnership()
2309: @*/
2310: PetscErrorCode MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
2311: {
2318: PetscTryMethod(B,"MatMPISBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,bs,d_nz,d_nnz,o_nz,o_nnz));
2319: return(0);
2320: }
2322: /*@C
2323: MatCreateSBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format
2324: (block compressed row). For good matrix assembly performance
2325: the user should preallocate the matrix storage by setting the parameters
2326: d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately,
2327: performance can be increased by more than a factor of 50.
2329: Collective
2331: Input Parameters:
2332: + comm - MPI communicator
2333: . bs - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
2334: blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
2335: . m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
2336: This value should be the same as the local size used in creating the
2337: y vector for the matrix-vector product y = Ax.
2338: . n - number of local columns (or PETSC_DECIDE to have calculated if N is given)
2339: This value should be the same as the local size used in creating the
2340: x vector for the matrix-vector product y = Ax.
2341: . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
2342: . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
2343: . d_nz - number of block nonzeros per block row in diagonal portion of local
2344: submatrix (same for all local rows)
2345: . d_nnz - array containing the number of block nonzeros in the various block rows
2346: in the upper triangular portion of the in diagonal portion of the local
2347: (possibly different for each block block row) or NULL.
2348: If you plan to factor the matrix you must leave room for the diagonal entry and
2349: set its value even if it is zero.
2350: . o_nz - number of block nonzeros per block row in the off-diagonal portion of local
2351: submatrix (same for all local rows).
2352: - o_nnz - array containing the number of nonzeros in the various block rows of the
2353: off-diagonal portion of the local submatrix (possibly different for
2354: each block row) or NULL.
2356: Output Parameter:
2357: . A - the matrix
2359: Options Database Keys:
2360: + -mat_no_unroll - uses code that does not unroll the loops in the
2361: block calculations (much slower)
2362: . -mat_block_size - size of the blocks to use
2363: - -mat_mpi - use the parallel matrix data structures even on one processor
2364: (defaults to using SeqBAIJ format on one processor)
2366: It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
2367: MatXXXXSetPreallocation() paradigm instead of this routine directly.
2368: [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]
2370: Notes:
2371: The number of rows and columns must be divisible by blocksize.
2372: This matrix type does not support complex Hermitian operation.
2374: The user MUST specify either the local or global matrix dimensions
2375: (possibly both).
2377: If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor
2378: than it must be used on all processors that share the object for that argument.
2380: If the *_nnz parameter is given then the *_nz parameter is ignored
2382: Storage Information:
2383: For a square global matrix we define each processor's diagonal portion
2384: to be its local rows and the corresponding columns (a square submatrix);
2385: each processor's off-diagonal portion encompasses the remainder of the
2386: local matrix (a rectangular submatrix).
2388: The user can specify preallocated storage for the diagonal part of
2389: the local submatrix with either d_nz or d_nnz (not both). Set
2390: d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
2391: memory allocation. Likewise, specify preallocated storage for the
2392: off-diagonal part of the local submatrix with o_nz or o_nnz (not both).
2394: Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
2395: the figure below we depict these three local rows and all columns (0-11).
2397: .vb
2398: 0 1 2 3 4 5 6 7 8 9 10 11
2399: --------------------------
2400: row 3 |. . . d d d o o o o o o
2401: row 4 |. . . d d d o o o o o o
2402: row 5 |. . . d d d o o o o o o
2403: --------------------------
2404: .ve
2406: Thus, any entries in the d locations are stored in the d (diagonal)
2407: submatrix, and any entries in the o locations are stored in the
2408: o (off-diagonal) submatrix. Note that the d matrix is stored in
2409: MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format.
2411: Now d_nz should indicate the number of block nonzeros per row in the upper triangular
2412: plus the diagonal part of the d matrix,
2413: and o_nz should indicate the number of block nonzeros per row in the o matrix.
2414: In general, for PDE problems in which most nonzeros are near the diagonal,
2415: one expects d_nz >> o_nz. For large problems you MUST preallocate memory
2416: or you will get TERRIBLE performance; see the users' manual chapter on
2417: matrices.
2419: Level: intermediate
2421: .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ()
2422: @*/
2424: 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)
2425: {
2427: PetscMPIInt size;
2430: MatCreate(comm,A);
2431: MatSetSizes(*A,m,n,M,N);
2432: MPI_Comm_size(comm,&size);
2433: if (size > 1) {
2434: MatSetType(*A,MATMPISBAIJ);
2435: MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);
2436: } else {
2437: MatSetType(*A,MATSEQSBAIJ);
2438: MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);
2439: }
2440: return(0);
2441: }
2444: static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
2445: {
2446: Mat mat;
2447: Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data;
2449: PetscInt len=0,nt,bs=matin->rmap->bs,mbs=oldmat->mbs;
2450: PetscScalar *array;
2453: *newmat = NULL;
2455: MatCreate(PetscObjectComm((PetscObject)matin),&mat);
2456: MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
2457: MatSetType(mat,((PetscObject)matin)->type_name);
2458: PetscLayoutReference(matin->rmap,&mat->rmap);
2459: PetscLayoutReference(matin->cmap,&mat->cmap);
2461: mat->factortype = matin->factortype;
2462: mat->preallocated = PETSC_TRUE;
2463: mat->assembled = PETSC_TRUE;
2464: mat->insertmode = NOT_SET_VALUES;
2466: a = (Mat_MPISBAIJ*)mat->data;
2467: a->bs2 = oldmat->bs2;
2468: a->mbs = oldmat->mbs;
2469: a->nbs = oldmat->nbs;
2470: a->Mbs = oldmat->Mbs;
2471: a->Nbs = oldmat->Nbs;
2473: a->size = oldmat->size;
2474: a->rank = oldmat->rank;
2475: a->donotstash = oldmat->donotstash;
2476: a->roworiented = oldmat->roworiented;
2477: a->rowindices = NULL;
2478: a->rowvalues = NULL;
2479: a->getrowactive = PETSC_FALSE;
2480: a->barray = NULL;
2481: a->rstartbs = oldmat->rstartbs;
2482: a->rendbs = oldmat->rendbs;
2483: a->cstartbs = oldmat->cstartbs;
2484: a->cendbs = oldmat->cendbs;
2486: /* hash table stuff */
2487: a->ht = NULL;
2488: a->hd = NULL;
2489: a->ht_size = 0;
2490: a->ht_flag = oldmat->ht_flag;
2491: a->ht_fact = oldmat->ht_fact;
2492: a->ht_total_ct = 0;
2493: a->ht_insert_ct = 0;
2495: PetscArraycpy(a->rangebs,oldmat->rangebs,a->size+2);
2496: if (oldmat->colmap) {
2497: #if defined(PETSC_USE_CTABLE)
2498: PetscTableCreateCopy(oldmat->colmap,&a->colmap);
2499: #else
2500: PetscMalloc1(a->Nbs,&a->colmap);
2501: PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));
2502: PetscArraycpy(a->colmap,oldmat->colmap,a->Nbs);
2503: #endif
2504: } else a->colmap = NULL;
2506: if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) {
2507: PetscMalloc1(len,&a->garray);
2508: PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));
2509: PetscArraycpy(a->garray,oldmat->garray,len);
2510: } else a->garray = NULL;
2512: MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);
2513: VecDuplicate(oldmat->lvec,&a->lvec);
2514: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);
2515: VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
2516: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);
2518: VecDuplicate(oldmat->slvec0,&a->slvec0);
2519: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);
2520: VecDuplicate(oldmat->slvec1,&a->slvec1);
2521: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);
2523: VecGetLocalSize(a->slvec1,&nt);
2524: VecGetArray(a->slvec1,&array);
2525: VecCreateSeqWithArray(PETSC_COMM_SELF,1,bs*mbs,array,&a->slvec1a);
2526: VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec1b);
2527: VecRestoreArray(a->slvec1,&array);
2528: VecGetArray(a->slvec0,&array);
2529: VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec0b);
2530: VecRestoreArray(a->slvec0,&array);
2531: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);
2532: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);
2533: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0b);
2534: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1a);
2535: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1b);
2537: /* VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */
2538: PetscObjectReference((PetscObject)oldmat->sMvctx);
2539: a->sMvctx = oldmat->sMvctx;
2540: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->sMvctx);
2542: MatDuplicate(oldmat->A,cpvalues,&a->A);
2543: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
2544: MatDuplicate(oldmat->B,cpvalues,&a->B);
2545: PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);
2546: PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
2547: *newmat = mat;
2548: return(0);
2549: }
2551: /* Used for both MPIBAIJ and MPISBAIJ matrices */
2552: #define MatLoad_MPISBAIJ_Binary MatLoad_MPIBAIJ_Binary
2554: PetscErrorCode MatLoad_MPISBAIJ(Mat mat,PetscViewer viewer)
2555: {
2557: PetscBool isbinary;
2560: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
2561: if (!isbinary) SETERRQ2(PetscObjectComm((PetscObject)viewer),PETSC_ERR_SUP,"Viewer type %s not yet supported for reading %s matrices",((PetscObject)viewer)->type_name,((PetscObject)mat)->type_name);
2562: MatLoad_MPISBAIJ_Binary(mat,viewer);
2563: return(0);
2564: }
2566: /*XXXXX@
2567: MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable.
2569: Input Parameters:
2570: . mat - the matrix
2571: . fact - factor
2573: Not Collective on Mat, each process can have a different hash factor
2575: Level: advanced
2577: Notes:
2578: This can also be set by the command line option: -mat_use_hash_table fact
2580: .seealso: MatSetOption()
2581: @XXXXX*/
2584: PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat A,Vec v,PetscInt idx[])
2585: {
2586: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
2587: Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data;
2588: PetscReal atmp;
2589: PetscReal *work,*svalues,*rvalues;
2591: PetscInt i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol;
2592: PetscMPIInt rank,size;
2593: PetscInt *rowners_bs,dest,count,source;
2594: PetscScalar *va;
2595: MatScalar *ba;
2596: MPI_Status stat;
2599: if (idx) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Send email to petsc-maint@mcs.anl.gov");
2600: MatGetRowMaxAbs(a->A,v,NULL);
2601: VecGetArray(v,&va);
2603: MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);
2604: MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);
2606: bs = A->rmap->bs;
2607: mbs = a->mbs;
2608: Mbs = a->Mbs;
2609: ba = b->a;
2610: bi = b->i;
2611: bj = b->j;
2613: /* find ownerships */
2614: rowners_bs = A->rmap->range;
2616: /* each proc creates an array to be distributed */
2617: PetscCalloc1(bs*Mbs,&work);
2619: /* row_max for B */
2620: if (rank != size-1) {
2621: for (i=0; i<mbs; i++) {
2622: ncols = bi[1] - bi[0]; bi++;
2623: brow = bs*i;
2624: for (j=0; j<ncols; j++) {
2625: bcol = bs*(*bj);
2626: for (kcol=0; kcol<bs; kcol++) {
2627: col = bcol + kcol; /* local col index */
2628: col += rowners_bs[rank+1]; /* global col index */
2629: for (krow=0; krow<bs; krow++) {
2630: atmp = PetscAbsScalar(*ba); ba++;
2631: row = brow + krow; /* local row index */
2632: if (PetscRealPart(va[row]) < atmp) va[row] = atmp;
2633: if (work[col] < atmp) work[col] = atmp;
2634: }
2635: }
2636: bj++;
2637: }
2638: }
2640: /* send values to its owners */
2641: for (dest=rank+1; dest<size; dest++) {
2642: svalues = work + rowners_bs[dest];
2643: count = rowners_bs[dest+1]-rowners_bs[dest];
2644: MPI_Send(svalues,count,MPIU_REAL,dest,rank,PetscObjectComm((PetscObject)A));
2645: }
2646: }
2648: /* receive values */
2649: if (rank) {
2650: rvalues = work;
2651: count = rowners_bs[rank+1]-rowners_bs[rank];
2652: for (source=0; source<rank; source++) {
2653: MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,PetscObjectComm((PetscObject)A),&stat);
2654: /* process values */
2655: for (i=0; i<count; i++) {
2656: if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i];
2657: }
2658: }
2659: }
2661: VecRestoreArray(v,&va);
2662: PetscFree(work);
2663: return(0);
2664: }
2666: PetscErrorCode MatSOR_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
2667: {
2668: Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data;
2669: PetscErrorCode ierr;
2670: PetscInt mbs=mat->mbs,bs=matin->rmap->bs;
2671: PetscScalar *x,*ptr,*from;
2672: Vec bb1;
2673: const PetscScalar *b;
2676: 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);
2677: if (bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented");
2679: if (flag == SOR_APPLY_UPPER) {
2680: (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
2681: return(0);
2682: }
2684: if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
2685: if (flag & SOR_ZERO_INITIAL_GUESS) {
2686: (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);
2687: its--;
2688: }
2690: VecDuplicate(bb,&bb1);
2691: while (its--) {
2693: /* lower triangular part: slvec0b = - B^T*xx */
2694: (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);
2696: /* copy xx into slvec0a */
2697: VecGetArray(mat->slvec0,&ptr);
2698: VecGetArray(xx,&x);
2699: PetscArraycpy(ptr,x,bs*mbs);
2700: VecRestoreArray(mat->slvec0,&ptr);
2702: VecScale(mat->slvec0,-1.0);
2704: /* copy bb into slvec1a */
2705: VecGetArray(mat->slvec1,&ptr);
2706: VecGetArrayRead(bb,&b);
2707: PetscArraycpy(ptr,b,bs*mbs);
2708: VecRestoreArray(mat->slvec1,&ptr);
2710: /* set slvec1b = 0 */
2711: VecSet(mat->slvec1b,0.0);
2713: VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
2714: VecRestoreArray(xx,&x);
2715: VecRestoreArrayRead(bb,&b);
2716: VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
2718: /* upper triangular part: bb1 = bb1 - B*x */
2719: (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);
2721: /* local diagonal sweep */
2722: (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);
2723: }
2724: VecDestroy(&bb1);
2725: } else if ((flag & SOR_LOCAL_FORWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) {
2726: (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
2727: } else if ((flag & SOR_LOCAL_BACKWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) {
2728: (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
2729: } else if (flag & SOR_EISENSTAT) {
2730: Vec xx1;
2731: PetscBool hasop;
2732: const PetscScalar *diag;
2733: PetscScalar *sl,scale = (omega - 2.0)/omega;
2734: PetscInt i,n;
2736: if (!mat->xx1) {
2737: VecDuplicate(bb,&mat->xx1);
2738: VecDuplicate(bb,&mat->bb1);
2739: }
2740: xx1 = mat->xx1;
2741: bb1 = mat->bb1;
2743: (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);
2745: if (!mat->diag) {
2746: /* this is wrong for same matrix with new nonzero values */
2747: MatCreateVecs(matin,&mat->diag,NULL);
2748: MatGetDiagonal(matin,mat->diag);
2749: }
2750: MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);
2752: if (hasop) {
2753: MatMultDiagonalBlock(matin,xx,bb1);
2754: VecAYPX(mat->slvec1a,scale,bb);
2755: } else {
2756: /*
2757: These two lines are replaced by code that may be a bit faster for a good compiler
2758: VecPointwiseMult(mat->slvec1a,mat->diag,xx);
2759: VecAYPX(mat->slvec1a,scale,bb);
2760: */
2761: VecGetArray(mat->slvec1a,&sl);
2762: VecGetArrayRead(mat->diag,&diag);
2763: VecGetArrayRead(bb,&b);
2764: VecGetArray(xx,&x);
2765: VecGetLocalSize(xx,&n);
2766: if (omega == 1.0) {
2767: for (i=0; i<n; i++) sl[i] = b[i] - diag[i]*x[i];
2768: PetscLogFlops(2.0*n);
2769: } else {
2770: for (i=0; i<n; i++) sl[i] = b[i] + scale*diag[i]*x[i];
2771: PetscLogFlops(3.0*n);
2772: }
2773: VecRestoreArray(mat->slvec1a,&sl);
2774: VecRestoreArrayRead(mat->diag,&diag);
2775: VecRestoreArrayRead(bb,&b);
2776: VecRestoreArray(xx,&x);
2777: }
2779: /* multiply off-diagonal portion of matrix */
2780: VecSet(mat->slvec1b,0.0);
2781: (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);
2782: VecGetArray(mat->slvec0,&from);
2783: VecGetArray(xx,&x);
2784: PetscArraycpy(from,x,bs*mbs);
2785: VecRestoreArray(mat->slvec0,&from);
2786: VecRestoreArray(xx,&x);
2787: VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
2788: VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);
2789: (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,mat->slvec1a);
2791: /* local sweep */
2792: (*mat->A->ops->sor)(mat->A,mat->slvec1a,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);
2793: VecAXPY(xx,1.0,xx1);
2794: } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format");
2795: return(0);
2796: }
2798: /*@
2799: MatCreateMPISBAIJWithArrays - creates a MPI SBAIJ matrix using arrays that contain in standard
2800: CSR format the local rows.
2802: Collective
2804: Input Parameters:
2805: + comm - MPI communicator
2806: . bs - the block size, only a block size of 1 is supported
2807: . m - number of local rows (Cannot be PETSC_DECIDE)
2808: . n - This value should be the same as the local size used in creating the
2809: x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
2810: calculated if N is given) For square matrices n is almost always m.
2811: . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
2812: . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
2813: . i - row indices; that is i[0] = 0, i[row] = i[row-1] + number of block elements in that row block row of the matrix
2814: . j - column indices
2815: - a - matrix values
2817: Output Parameter:
2818: . mat - the matrix
2820: Level: intermediate
2822: Notes:
2823: The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
2824: thus you CANNOT change the matrix entries by changing the values of a[] after you have
2825: called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.
2827: The i and j indices are 0 based, and i indices are indices corresponding to the local j array.
2829: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
2830: MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays()
2831: @*/
2832: 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)
2833: {
2838: if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
2839: if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
2840: MatCreate(comm,mat);
2841: MatSetSizes(*mat,m,n,M,N);
2842: MatSetType(*mat,MATMPISBAIJ);
2843: MatMPISBAIJSetPreallocationCSR(*mat,bs,i,j,a);
2844: return(0);
2845: }
2848: /*@C
2849: MatMPISBAIJSetPreallocationCSR - Creates a sparse parallel matrix in SBAIJ format using the given nonzero structure and (optional) numerical values
2851: Collective
2853: Input Parameters:
2854: + B - the matrix
2855: . bs - the block size
2856: . i - the indices into j for the start of each local row (starts with zero)
2857: . j - the column indices for each local row (starts with zero) these must be sorted for each row
2858: - v - optional values in the matrix
2860: Level: advanced
2862: Notes:
2863: Though this routine has Preallocation() in the name it also sets the exact nonzero locations of the matrix entries
2864: and usually the numerical values as well
2866: Any entries below the diagonal are ignored
2868: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ
2869: @*/
2870: PetscErrorCode MatMPISBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
2871: {
2875: PetscTryMethod(B,"MatMPISBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));
2876: return(0);
2877: }
2879: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPISBAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
2880: {
2882: PetscInt m,N,i,rstart,nnz,Ii,bs,cbs;
2883: PetscInt *indx;
2884: PetscScalar *values;
2887: MatGetSize(inmat,&m,&N);
2888: if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */
2889: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)inmat->data;
2890: PetscInt *dnz,*onz,mbs,Nbs,nbs;
2891: PetscInt *bindx,rmax=a->rmax,j;
2892: PetscMPIInt rank,size;
2894: MatGetBlockSizes(inmat,&bs,&cbs);
2895: mbs = m/bs; Nbs = N/cbs;
2896: if (n == PETSC_DECIDE) {
2897: PetscSplitOwnershipBlock(comm,cbs,&n,&N);
2898: }
2899: nbs = n/cbs;
2901: PetscMalloc1(rmax,&bindx);
2902: MatPreallocateInitialize(comm,mbs,nbs,dnz,onz); /* inline function, output __end and __rstart are used below */
2904: MPI_Comm_rank(comm,&rank);
2905: MPI_Comm_rank(comm,&size);
2906: if (rank == size-1) {
2907: /* Check sum(nbs) = Nbs */
2908: if (__end != Nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local block columns %D != global block columns %D",__end,Nbs);
2909: }
2911: rstart = __rstart; /* block rstart of *outmat; see inline function MatPreallocateInitialize */
2912: MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
2913: for (i=0; i<mbs; i++) {
2914: MatGetRow_SeqSBAIJ(inmat,i*bs,&nnz,&indx,NULL); /* non-blocked nnz and indx */
2915: nnz = nnz/bs;
2916: for (j=0; j<nnz; j++) bindx[j] = indx[j*bs]/bs;
2917: MatPreallocateSet(i+rstart,nnz,bindx,dnz,onz);
2918: MatRestoreRow_SeqSBAIJ(inmat,i*bs,&nnz,&indx,NULL);
2919: }
2920: MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
2921: PetscFree(bindx);
2923: MatCreate(comm,outmat);
2924: MatSetSizes(*outmat,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
2925: MatSetBlockSizes(*outmat,bs,cbs);
2926: MatSetType(*outmat,MATSBAIJ);
2927: MatSeqSBAIJSetPreallocation(*outmat,bs,0,dnz);
2928: MatMPISBAIJSetPreallocation(*outmat,bs,0,dnz,0,onz);
2929: MatPreallocateFinalize(dnz,onz);
2930: }
2932: /* numeric phase */
2933: MatGetBlockSizes(inmat,&bs,&cbs);
2934: MatGetOwnershipRange(*outmat,&rstart,NULL);
2936: MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_TRUE);
2937: for (i=0; i<m; i++) {
2938: MatGetRow_SeqSBAIJ(inmat,i,&nnz,&indx,&values);
2939: Ii = i + rstart;
2940: MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);
2941: MatRestoreRow_SeqSBAIJ(inmat,i,&nnz,&indx,&values);
2942: }
2943: MatSetOption(inmat,MAT_GETROW_UPPERTRIANGULAR,PETSC_FALSE);
2944: MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);
2945: MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);
2946: return(0);
2947: }