Actual source code: mpisbaij.c
1: #define PETSCMAT_DLL
3: #include src/mat/impls/baij/mpi/mpibaij.h
4: #include mpisbaij.h
5: #include src/mat/impls/sbaij/seq/sbaij.h
7: EXTERN PetscErrorCode MatSetUpMultiply_MPISBAIJ(Mat);
8: EXTERN PetscErrorCode MatSetUpMultiply_MPISBAIJ_2comm(Mat);
9: EXTERN PetscErrorCode DisAssemble_MPISBAIJ(Mat);
10: EXTERN PetscErrorCode MatIncreaseOverlap_MPISBAIJ(Mat,PetscInt,IS[],PetscInt);
11: EXTERN PetscErrorCode MatGetValues_SeqSBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],PetscScalar []);
12: EXTERN PetscErrorCode MatGetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],PetscScalar []);
13: EXTERN PetscErrorCode MatSetValues_SeqSBAIJ(Mat,PetscInt,const PetscInt [],PetscInt,const PetscInt [],const PetscScalar [],InsertMode);
14: EXTERN PetscErrorCode MatSetValuesBlocked_SeqSBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
15: EXTERN PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
16: EXTERN PetscErrorCode MatGetRow_SeqSBAIJ(Mat,PetscInt,PetscInt*,PetscInt**,PetscScalar**);
17: EXTERN PetscErrorCode MatRestoreRow_SeqSBAIJ(Mat,PetscInt,PetscInt*,PetscInt**,PetscScalar**);
18: EXTERN PetscErrorCode MatZeroRows_SeqSBAIJ(Mat,IS,PetscScalar*);
19: EXTERN PetscErrorCode MatZeroRows_SeqBAIJ(Mat,IS,PetscScalar *);
20: EXTERN PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat,Vec,PetscInt[]);
21: EXTERN PetscErrorCode MatRelax_MPISBAIJ(Mat,Vec,PetscReal,MatSORType,PetscReal,PetscInt,PetscInt,Vec);
23: /* UGLY, ugly, ugly
24: When MatScalar == PetscScalar the function MatSetValuesBlocked_MPIBAIJ_MatScalar() does
25: not exist. Otherwise ..._MatScalar() takes matrix elements in single precision and
26: inserts them into the single precision data structure. The function MatSetValuesBlocked_MPIBAIJ()
27: converts the entries into single precision and then calls ..._MatScalar() to put them
28: into the single precision data structures.
29: */
30: #if defined(PETSC_USE_MAT_SINGLE)
31: EXTERN PetscErrorCode MatSetValuesBlocked_SeqSBAIJ_MatScalar(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const MatScalar[],InsertMode);
32: EXTERN PetscErrorCode MatSetValues_MPISBAIJ_MatScalar(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const MatScalar[],InsertMode);
33: EXTERN PetscErrorCode MatSetValuesBlocked_MPISBAIJ_MatScalar(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const MatScalar[],InsertMode);
34: EXTERN PetscErrorCode MatSetValues_MPISBAIJ_HT_MatScalar(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const MatScalar[],InsertMode);
35: EXTERN PetscErrorCode MatSetValuesBlocked_MPISBAIJ_HT_MatScalar(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const MatScalar[],InsertMode);
36: #else
37: #define MatSetValuesBlocked_SeqSBAIJ_MatScalar MatSetValuesBlocked_SeqSBAIJ
38: #define MatSetValues_MPISBAIJ_MatScalar MatSetValues_MPISBAIJ
39: #define MatSetValuesBlocked_MPISBAIJ_MatScalar MatSetValuesBlocked_MPISBAIJ
40: #define MatSetValues_MPISBAIJ_HT_MatScalar MatSetValues_MPISBAIJ_HT
41: #define MatSetValuesBlocked_MPISBAIJ_HT_MatScalar MatSetValuesBlocked_MPISBAIJ_HT
42: #endif
47: PetscErrorCode MatStoreValues_MPISBAIJ(Mat mat)
48: {
49: Mat_MPISBAIJ *aij = (Mat_MPISBAIJ *)mat->data;
53: MatStoreValues(aij->A);
54: MatStoreValues(aij->B);
55: return(0);
56: }
62: PetscErrorCode MatRetrieveValues_MPISBAIJ(Mat mat)
63: {
64: Mat_MPISBAIJ *aij = (Mat_MPISBAIJ *)mat->data;
68: MatRetrieveValues(aij->A);
69: MatRetrieveValues(aij->B);
70: return(0);
71: }
75: #define CHUNKSIZE 10
77: #define MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv) \
78: { \
79: \
80: brow = row/bs; \
81: rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \
82: rmax = aimax[brow]; nrow = ailen[brow]; \
83: bcol = col/bs; \
84: ridx = row % bs; cidx = col % bs; \
85: low = 0; high = nrow; \
86: while (high-low > 3) { \
87: t = (low+high)/2; \
88: if (rp[t] > bcol) high = t; \
89: else low = t; \
90: } \
91: for (_i=low; _i<high; _i++) { \
92: if (rp[_i] > bcol) break; \
93: if (rp[_i] == bcol) { \
94: bap = ap + bs2*_i + bs*cidx + ridx; \
95: if (addv == ADD_VALUES) *bap += value; \
96: else *bap = value; \
97: goto a_noinsert; \
98: } \
99: } \
100: if (a->nonew == 1) goto a_noinsert; \
101: if (a->nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \
102: MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \
103: N = nrow++ - 1; \
104: /* shift up all the later entries in this row */ \
105: for (ii=N; ii>=_i; ii--) { \
106: rp[ii+1] = rp[ii]; \
107: PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar)); \
108: } \
109: if (N>=_i) { PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar)); } \
110: rp[_i] = bcol; \
111: ap[bs2*_i + bs*cidx + ridx] = value; \
112: a_noinsert:; \
113: ailen[brow] = nrow; \
114: }
115: #ifndef MatSetValues_SeqBAIJ_B_Private
116: #define MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv) \
117: { \
118: brow = row/bs; \
119: rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \
120: rmax = bimax[brow]; nrow = bilen[brow]; \
121: bcol = col/bs; \
122: ridx = row % bs; cidx = col % bs; \
123: low = 0; high = nrow; \
124: while (high-low > 3) { \
125: t = (low+high)/2; \
126: if (rp[t] > bcol) high = t; \
127: else low = t; \
128: } \
129: for (_i=low; _i<high; _i++) { \
130: if (rp[_i] > bcol) break; \
131: if (rp[_i] == bcol) { \
132: bap = ap + bs2*_i + bs*cidx + ridx; \
133: if (addv == ADD_VALUES) *bap += value; \
134: else *bap = value; \
135: goto b_noinsert; \
136: } \
137: } \
138: if (b->nonew == 1) goto b_noinsert; \
139: if (b->nonew == -1) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \
140: MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \
141: N = nrow++ - 1; \
142: /* shift up all the later entries in this row */ \
143: for (ii=N; ii>=_i; ii--) { \
144: rp[ii+1] = rp[ii]; \
145: PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar)); \
146: } \
147: if (N>=_i) { PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));} \
148: rp[_i] = bcol; \
149: ap[bs2*_i + bs*cidx + ridx] = value; \
150: b_noinsert:; \
151: bilen[brow] = nrow; \
152: }
153: #endif
155: #if defined(PETSC_USE_MAT_SINGLE)
158: PetscErrorCode MatSetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
159: {
160: Mat_MPISBAIJ *b = (Mat_MPISBAIJ*)mat->data;
162: PetscInt i,N = m*n;
163: MatScalar *vsingle;
166: if (N > b->setvalueslen) {
167: PetscFree(b->setvaluescopy);
168: PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);
169: b->setvalueslen = N;
170: }
171: vsingle = b->setvaluescopy;
173: for (i=0; i<N; i++) {
174: vsingle[i] = v[i];
175: }
176: MatSetValues_MPISBAIJ_MatScalar(mat,m,im,n,in,vsingle,addv);
177: return(0);
178: }
182: PetscErrorCode MatSetValuesBlocked_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
183: {
184: Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data;
186: PetscInt i,N = m*n*b->bs2;
187: MatScalar *vsingle;
190: if (N > b->setvalueslen) {
191: PetscFree(b->setvaluescopy);
192: PetscMalloc(N*sizeof(MatScalar),&b->setvaluescopy);
193: b->setvalueslen = N;
194: }
195: vsingle = b->setvaluescopy;
196: for (i=0; i<N; i++) {
197: vsingle[i] = v[i];
198: }
199: MatSetValuesBlocked_MPISBAIJ_MatScalar(mat,m,im,n,in,vsingle,addv);
200: return(0);
201: }
202: #endif
204: /* Only add/insert a(i,j) with i<=j (blocks).
205: Any a(i,j) with i>j input by user is ingored.
206: */
209: PetscErrorCode MatSetValues_MPISBAIJ_MatScalar(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv)
210: {
211: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
212: MatScalar value;
213: PetscTruth roworiented = baij->roworiented;
215: PetscInt i,j,row,col;
216: PetscInt rstart_orig=mat->rmap.rstart;
217: PetscInt rend_orig=mat->rmap.rend,cstart_orig=mat->cmap.rstart;
218: PetscInt cend_orig=mat->cmap.rend,bs=mat->rmap.bs;
220: /* Some Variables required in the macro */
221: Mat A = baij->A;
222: Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)(A)->data;
223: PetscInt *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j;
224: MatScalar *aa=a->a;
226: Mat B = baij->B;
227: Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data;
228: PetscInt *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j;
229: MatScalar *ba=b->a;
231: PetscInt *rp,ii,nrow,_i,rmax,N,brow,bcol;
232: PetscInt low,high,t,ridx,cidx,bs2=a->bs2;
233: MatScalar *ap,*bap;
235: /* for stash */
236: PetscInt n_loc, *in_loc = PETSC_NULL;
237: MatScalar *v_loc = PETSC_NULL;
241: if (!baij->donotstash){
242: if (n > baij->n_loc) {
243: PetscFree(baij->in_loc);
244: PetscFree(baij->v_loc);
245: PetscMalloc(n*sizeof(PetscInt),&baij->in_loc);
246: PetscMalloc(n*sizeof(MatScalar),&baij->v_loc);
247: baij->n_loc = n;
248: }
249: in_loc = baij->in_loc;
250: v_loc = baij->v_loc;
251: }
253: for (i=0; i<m; i++) {
254: if (im[i] < 0) continue;
255: #if defined(PETSC_USE_DEBUG)
256: if (im[i] >= mat->rmap.N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap.N-1);
257: #endif
258: if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */
259: row = im[i] - rstart_orig; /* local row index */
260: for (j=0; j<n; j++) {
261: if (im[i]/bs > in[j]/bs){
262: if (a->ignore_ltriangular){
263: continue; /* ignore lower triangular blocks */
264: } else {
265: SETERRQ(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)");
266: }
267: }
268: if (in[j] >= cstart_orig && in[j] < cend_orig){ /* diag entry (A) */
269: col = in[j] - cstart_orig; /* local col index */
270: brow = row/bs; bcol = col/bs;
271: if (brow > bcol) continue; /* ignore lower triangular blocks of A */
272: if (roworiented) value = v[i*n+j]; else value = v[i+j*m];
273: MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv);
274: /* MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv); */
275: } else if (in[j] < 0) continue;
276: #if defined(PETSC_USE_DEBUG)
277: else if (in[j] >= mat->cmap.N) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap.N-1);}
278: #endif
279: else { /* off-diag entry (B) */
280: if (mat->was_assembled) {
281: if (!baij->colmap) {
282: CreateColmap_MPIBAIJ_Private(mat);
283: }
284: #if defined (PETSC_USE_CTABLE)
285: PetscTableFind(baij->colmap,in[j]/bs + 1,&col);
286: col = col - 1;
287: #else
288: col = baij->colmap[in[j]/bs] - 1;
289: #endif
290: if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) {
291: DisAssemble_MPISBAIJ(mat);
292: col = in[j];
293: /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */
294: B = baij->B;
295: b = (Mat_SeqBAIJ*)(B)->data;
296: bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j;
297: ba=b->a;
298: } else col += in[j]%bs;
299: } else col = in[j];
300: if (roworiented) value = v[i*n+j]; else value = v[i+j*m];
301: MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv);
302: /* MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv); */
303: }
304: }
305: } else { /* off processor entry */
306: if (!baij->donotstash) {
307: n_loc = 0;
308: for (j=0; j<n; j++){
309: if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */
310: in_loc[n_loc] = in[j];
311: if (roworiented) {
312: v_loc[n_loc] = v[i*n+j];
313: } else {
314: v_loc[n_loc] = v[j*m+i];
315: }
316: n_loc++;
317: }
318: MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc);
319: }
320: }
321: }
322: return(0);
323: }
327: PetscErrorCode MatSetValuesBlocked_MPISBAIJ_MatScalar(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv)
328: {
329: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
330: const MatScalar *value;
331: MatScalar *barray=baij->barray;
332: PetscTruth roworiented = baij->roworiented;
333: PetscErrorCode ierr;
334: PetscInt i,j,ii,jj,row,col,rstart=baij->rstartbs;
335: PetscInt rend=baij->rendbs,cstart=baij->rstartbs,stepval;
336: PetscInt cend=baij->rendbs,bs=mat->rmap.bs,bs2=baij->bs2;
339: if(!barray) {
340: PetscMalloc(bs2*sizeof(MatScalar),&barray);
341: baij->barray = barray;
342: }
344: if (roworiented) {
345: stepval = (n-1)*bs;
346: } else {
347: stepval = (m-1)*bs;
348: }
349: for (i=0; i<m; i++) {
350: if (im[i] < 0) continue;
351: #if defined(PETSC_USE_DEBUG)
352: if (im[i] >= baij->Mbs) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %D max %D",im[i],baij->Mbs-1);
353: #endif
354: if (im[i] >= rstart && im[i] < rend) {
355: row = im[i] - rstart;
356: for (j=0; j<n; j++) {
357: /* If NumCol = 1 then a copy is not required */
358: if ((roworiented) && (n == 1)) {
359: barray = (MatScalar*) v + i*bs2;
360: } else if((!roworiented) && (m == 1)) {
361: barray = (MatScalar*) v + j*bs2;
362: } else { /* Here a copy is required */
363: if (roworiented) {
364: value = v + i*(stepval+bs)*bs + j*bs;
365: } else {
366: value = v + j*(stepval+bs)*bs + i*bs;
367: }
368: for (ii=0; ii<bs; ii++,value+=stepval) {
369: for (jj=0; jj<bs; jj++) {
370: *barray++ = *value++;
371: }
372: }
373: barray -=bs2;
374: }
375:
376: if (in[j] >= cstart && in[j] < cend){
377: col = in[j] - cstart;
378: MatSetValuesBlocked_SeqSBAIJ(baij->A,1,&row,1,&col,barray,addv);
379: }
380: else if (in[j] < 0) continue;
381: #if defined(PETSC_USE_DEBUG)
382: else if (in[j] >= baij->Nbs) {SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %D max %D",in[j],baij->Nbs-1);}
383: #endif
384: else {
385: if (mat->was_assembled) {
386: if (!baij->colmap) {
387: CreateColmap_MPIBAIJ_Private(mat);
388: }
390: #if defined(PETSC_USE_DEBUG)
391: #if defined (PETSC_USE_CTABLE)
392: { PetscInt data;
393: PetscTableFind(baij->colmap,in[j]+1,&data);
394: if ((data - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap");
395: }
396: #else
397: if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_ERR_PLIB,"Incorrect colmap");
398: #endif
399: #endif
400: #if defined (PETSC_USE_CTABLE)
401: PetscTableFind(baij->colmap,in[j]+1,&col);
402: col = (col - 1)/bs;
403: #else
404: col = (baij->colmap[in[j]] - 1)/bs;
405: #endif
406: if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
407: DisAssemble_MPISBAIJ(mat);
408: col = in[j];
409: }
410: }
411: else col = in[j];
412: MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);
413: }
414: }
415: } else {
416: if (!baij->donotstash) {
417: if (roworiented) {
418: MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
419: } else {
420: MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);
421: }
422: }
423: }
424: }
425: return(0);
426: }
430: PetscErrorCode MatGetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
431: {
432: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
434: PetscInt bs=mat->rmap.bs,i,j,bsrstart = mat->rmap.rstart,bsrend = mat->rmap.rend;
435: PetscInt bscstart = mat->cmap.rstart,bscend = mat->cmap.rend,row,col,data;
438: for (i=0; i<m; i++) {
439: if (idxm[i] < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);
440: if (idxm[i] >= mat->rmap.N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap.N-1);
441: if (idxm[i] >= bsrstart && idxm[i] < bsrend) {
442: row = idxm[i] - bsrstart;
443: for (j=0; j<n; j++) {
444: if (idxn[j] < 0) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Negative column %D",idxn[j]);
445: if (idxn[j] >= mat->cmap.N) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap.N-1);
446: if (idxn[j] >= bscstart && idxn[j] < bscend){
447: col = idxn[j] - bscstart;
448: MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);
449: } else {
450: if (!baij->colmap) {
451: CreateColmap_MPIBAIJ_Private(mat);
452: }
453: #if defined (PETSC_USE_CTABLE)
454: PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);
455: data --;
456: #else
457: data = baij->colmap[idxn[j]/bs]-1;
458: #endif
459: if((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0;
460: else {
461: col = data + idxn[j]%bs;
462: MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);
463: }
464: }
465: }
466: } else {
467: SETERRQ(PETSC_ERR_SUP,"Only local values currently supported");
468: }
469: }
470: return(0);
471: }
475: PetscErrorCode MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm)
476: {
477: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
479: PetscReal sum[2],*lnorm2;
482: if (baij->size == 1) {
483: MatNorm(baij->A,type,norm);
484: } else {
485: if (type == NORM_FROBENIUS) {
486: PetscMalloc(2*sizeof(PetscReal),&lnorm2);
487: MatNorm(baij->A,type,lnorm2);
488: *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++; /* squar power of norm(A) */
489: MatNorm(baij->B,type,lnorm2);
490: *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--; /* squar power of norm(B) */
491: MPI_Allreduce(lnorm2,&sum,2,MPIU_REAL,MPI_SUM,mat->comm);
492: *norm = sqrt(sum[0] + 2*sum[1]);
493: PetscFree(lnorm2);
494: } else if (type == NORM_INFINITY || type == NORM_1) { /* max row/column sum */
495: Mat_SeqSBAIJ *amat=(Mat_SeqSBAIJ*)baij->A->data;
496: Mat_SeqBAIJ *bmat=(Mat_SeqBAIJ*)baij->B->data;
497: PetscReal *rsum,*rsum2,vabs;
498: PetscInt *jj,*garray=baij->garray,rstart=baij->rstartbs,nz;
499: PetscInt brow,bcol,col,bs=baij->A->rmap.bs,row,grow,gcol,mbs=amat->mbs;
500: MatScalar *v;
502: PetscMalloc((2*mat->cmap.N+1)*sizeof(PetscReal),&rsum);
503: rsum2 = rsum + mat->cmap.N;
504: PetscMemzero(rsum,mat->cmap.N*sizeof(PetscReal));
505: /* Amat */
506: v = amat->a; jj = amat->j;
507: for (brow=0; brow<mbs; brow++) {
508: grow = bs*(rstart + brow);
509: nz = amat->i[brow+1] - amat->i[brow];
510: for (bcol=0; bcol<nz; bcol++){
511: gcol = bs*(rstart + *jj); jj++;
512: for (col=0; col<bs; col++){
513: for (row=0; row<bs; row++){
514: vabs = PetscAbsScalar(*v); v++;
515: rsum[gcol+col] += vabs;
516: /* non-diagonal block */
517: if (bcol > 0 && vabs > 0.0) rsum[grow+row] += vabs;
518: }
519: }
520: }
521: }
522: /* Bmat */
523: v = bmat->a; jj = bmat->j;
524: for (brow=0; brow<mbs; brow++) {
525: grow = bs*(rstart + brow);
526: nz = bmat->i[brow+1] - bmat->i[brow];
527: for (bcol=0; bcol<nz; bcol++){
528: gcol = bs*garray[*jj]; jj++;
529: for (col=0; col<bs; col++){
530: for (row=0; row<bs; row++){
531: vabs = PetscAbsScalar(*v); v++;
532: rsum[gcol+col] += vabs;
533: rsum[grow+row] += vabs;
534: }
535: }
536: }
537: }
538: MPI_Allreduce(rsum,rsum2,mat->cmap.N,MPIU_REAL,MPI_SUM,mat->comm);
539: *norm = 0.0;
540: for (col=0; col<mat->cmap.N; col++) {
541: if (rsum2[col] > *norm) *norm = rsum2[col];
542: }
543: PetscFree(rsum);
544: } else {
545: SETERRQ(PETSC_ERR_SUP,"No support for this norm yet");
546: }
547: }
548: return(0);
549: }
553: PetscErrorCode MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode)
554: {
555: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
557: PetscInt nstash,reallocs;
558: InsertMode addv;
561: if (baij->donotstash) {
562: return(0);
563: }
565: /* make sure all processors are either in INSERTMODE or ADDMODE */
566: MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,mat->comm);
567: if (addv == (ADD_VALUES|INSERT_VALUES)) {
568: SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added");
569: }
570: mat->insertmode = addv; /* in case this processor had no cache */
572: MatStashScatterBegin_Private(&mat->stash,mat->rmap.range);
573: MatStashScatterBegin_Private(&mat->bstash,baij->rangebs);
574: MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
575: PetscInfo2(0,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);
576: MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
577: PetscInfo2(0,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
578: return(0);
579: }
583: PetscErrorCode MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode)
584: {
585: Mat_MPISBAIJ *baij=(Mat_MPISBAIJ*)mat->data;
586: Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)baij->A->data;
588: PetscInt i,j,rstart,ncols,flg,bs2=baij->bs2;
589: PetscInt *row,*col,other_disassembled;
590: PetscMPIInt n;
591: PetscTruth r1,r2,r3;
592: MatScalar *val;
593: InsertMode addv = mat->insertmode;
595: /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */
598: if (!baij->donotstash) {
599: while (1) {
600: MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);
601: if (!flg) break;
603: for (i=0; i<n;) {
604: /* Now identify the consecutive vals belonging to the same row */
605: for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; }
606: if (j < n) ncols = j-i;
607: else ncols = n-i;
608: /* Now assemble all these values with a single function call */
609: MatSetValues_MPISBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i,addv);
610: i = j;
611: }
612: }
613: MatStashScatterEnd_Private(&mat->stash);
614: /* Now process the block-stash. Since the values are stashed column-oriented,
615: set the roworiented flag to column oriented, and after MatSetValues()
616: restore the original flags */
617: r1 = baij->roworiented;
618: r2 = a->roworiented;
619: r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented;
620: baij->roworiented = PETSC_FALSE;
621: a->roworiented = PETSC_FALSE;
622: ((Mat_SeqBAIJ*)baij->B->data)->roworiented = PETSC_FALSE; /* b->roworinted */
623: while (1) {
624: MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);
625: if (!flg) break;
626:
627: for (i=0; i<n;) {
628: /* Now identify the consecutive vals belonging to the same row */
629: for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; }
630: if (j < n) ncols = j-i;
631: else ncols = n-i;
632: MatSetValuesBlocked_MPISBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i*bs2,addv);
633: i = j;
634: }
635: }
636: MatStashScatterEnd_Private(&mat->bstash);
637: baij->roworiented = r1;
638: a->roworiented = r2;
639: ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworinted */
640: }
642: MatAssemblyBegin(baij->A,mode);
643: MatAssemblyEnd(baij->A,mode);
645: /* determine if any processor has disassembled, if so we must
646: also disassemble ourselfs, in order that we may reassemble. */
647: /*
648: if nonzero structure of submatrix B cannot change then we know that
649: no processor disassembled thus we can skip this stuff
650: */
651: if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) {
652: MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,mat->comm);
653: if (mat->was_assembled && !other_disassembled) {
654: DisAssemble_MPISBAIJ(mat);
655: }
656: }
658: if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
659: MatSetUpMultiply_MPISBAIJ(mat); /* setup Mvctx and sMvctx */
660: }
661: ((Mat_SeqBAIJ*)baij->B->data)->compressedrow.use = PETSC_TRUE; /* b->compressedrow.use */
662: MatAssemblyBegin(baij->B,mode);
663: MatAssemblyEnd(baij->B,mode);
664:
665: PetscFree(baij->rowvalues);
666: baij->rowvalues = 0;
668: return(0);
669: }
674: static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
675: {
676: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
677: PetscErrorCode ierr;
678: PetscInt bs = mat->rmap.bs;
679: PetscMPIInt size = baij->size,rank = baij->rank;
680: PetscTruth iascii,isdraw;
681: PetscViewer sviewer;
682: PetscViewerFormat format;
685: PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);
686: PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);
687: if (iascii) {
688: PetscViewerGetFormat(viewer,&format);
689: if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
690: MatInfo info;
691: MPI_Comm_rank(mat->comm,&rank);
692: MatGetInfo(mat,MAT_LOCAL,&info);
693: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n",
694: rank,mat->rmap.N,(PetscInt)info.nz_used*bs,(PetscInt)info.nz_allocated*bs,
695: mat->rmap.bs,(PetscInt)info.memory);
696: MatGetInfo(baij->A,MAT_LOCAL,&info);
697: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used*bs);
698: MatGetInfo(baij->B,MAT_LOCAL,&info);
699: PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used*bs);
700: PetscViewerFlush(viewer);
701: PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
702: VecScatterView(baij->Mvctx,viewer);
703: return(0);
704: } else if (format == PETSC_VIEWER_ASCII_INFO) {
705: PetscViewerASCIIPrintf(viewer," block size is %D\n",bs);
706: return(0);
707: } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
708: return(0);
709: }
710: }
712: if (isdraw) {
713: PetscDraw draw;
714: PetscTruth isnull;
715: PetscViewerDrawGetDraw(viewer,0,&draw);
716: PetscDrawIsNull(draw,&isnull); if (isnull) return(0);
717: }
719: if (size == 1) {
720: PetscObjectSetName((PetscObject)baij->A,mat->name);
721: MatView(baij->A,viewer);
722: } else {
723: /* assemble the entire matrix onto first processor. */
724: Mat A;
725: Mat_SeqSBAIJ *Aloc;
726: Mat_SeqBAIJ *Bloc;
727: PetscInt M = mat->rmap.N,N = mat->cmap.N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs;
728: MatScalar *a;
730: /* Should this be the same type as mat? */
731: MatCreate(mat->comm,&A);
732: if (!rank) {
733: MatSetSizes(A,M,N,M,N);
734: } else {
735: MatSetSizes(A,0,0,M,N);
736: }
737: MatSetType(A,MATMPISBAIJ);
738: MatMPISBAIJSetPreallocation(A,mat->rmap.bs,0,PETSC_NULL,0,PETSC_NULL);
739: PetscLogObjectParent(mat,A);
741: /* copy over the A part */
742: Aloc = (Mat_SeqSBAIJ*)baij->A->data;
743: ai = Aloc->i; aj = Aloc->j; a = Aloc->a;
744: PetscMalloc(bs*sizeof(PetscInt),&rvals);
746: for (i=0; i<mbs; i++) {
747: rvals[0] = bs*(baij->rstartbs + i);
748: for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; }
749: for (j=ai[i]; j<ai[i+1]; j++) {
750: col = (baij->cstartbs+aj[j])*bs;
751: for (k=0; k<bs; k++) {
752: MatSetValues_MPISBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);
753: col++; a += bs;
754: }
755: }
756: }
757: /* copy over the B part */
758: Bloc = (Mat_SeqBAIJ*)baij->B->data;
759: ai = Bloc->i; aj = Bloc->j; a = Bloc->a;
760: for (i=0; i<mbs; i++) {
761:
762: rvals[0] = bs*(baij->rstartbs + i);
763: for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; }
764: for (j=ai[i]; j<ai[i+1]; j++) {
765: col = baij->garray[aj[j]]*bs;
766: for (k=0; k<bs; k++) {
767: MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);
768: col++; a += bs;
769: }
770: }
771: }
772: PetscFree(rvals);
773: MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
774: MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
775: /*
776: Everyone has to call to draw the matrix since the graphics waits are
777: synchronized across all processors that share the PetscDraw object
778: */
779: PetscViewerGetSingleton(viewer,&sviewer);
780: if (!rank) {
781: PetscObjectSetName((PetscObject)((Mat_MPISBAIJ*)(A->data))->A,mat->name);
782: MatView(((Mat_MPISBAIJ*)(A->data))->A,sviewer);
783: }
784: PetscViewerRestoreSingleton(viewer,&sviewer);
785: MatDestroy(A);
786: }
787: return(0);
788: }
792: PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer)
793: {
795: PetscTruth iascii,isdraw,issocket,isbinary;
798: PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);
799: PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);
800: PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);
801: PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_BINARY,&isbinary);
802: if (iascii || isdraw || issocket || isbinary) {
803: MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);
804: } else {
805: SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported by MPISBAIJ matrices",((PetscObject)viewer)->type_name);
806: }
807: return(0);
808: }
812: PetscErrorCode MatDestroy_MPISBAIJ(Mat mat)
813: {
814: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
818: #if defined(PETSC_USE_LOG)
819: PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap.N,mat->cmap.N);
820: #endif
821: MatStashDestroy_Private(&mat->stash);
822: MatStashDestroy_Private(&mat->bstash);
823: MatDestroy(baij->A);
824: MatDestroy(baij->B);
825: #if defined (PETSC_USE_CTABLE)
826: if (baij->colmap) {PetscTableDestroy(baij->colmap);}
827: #else
828: PetscFree(baij->colmap);
829: #endif
830: PetscFree(baij->garray);
831: if (baij->lvec) {VecDestroy(baij->lvec);}
832: if (baij->Mvctx) {VecScatterDestroy(baij->Mvctx);}
833: if (baij->slvec0) {
834: VecDestroy(baij->slvec0);
835: VecDestroy(baij->slvec0b);
836: }
837: if (baij->slvec1) {
838: VecDestroy(baij->slvec1);
839: VecDestroy(baij->slvec1a);
840: VecDestroy(baij->slvec1b);
841: }
842: if (baij->sMvctx) {VecScatterDestroy(baij->sMvctx);}
843: PetscFree(baij->rowvalues);
844: PetscFree(baij->barray);
845: PetscFree(baij->hd);
846: #if defined(PETSC_USE_MAT_SINGLE)
847: PetscFree(baij->setvaluescopy);
848: #endif
849: PetscFree(baij->in_loc);
850: PetscFree(baij->v_loc);
851: PetscFree(baij->rangebs);
852: PetscFree(baij);
854: PetscObjectChangeTypeName((PetscObject)mat,0);
855: PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C","",PETSC_NULL);
856: PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C","",PETSC_NULL);
857: PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C","",PETSC_NULL);
858: PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C","",PETSC_NULL);
859: return(0);
860: }
864: PetscErrorCode MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy)
865: {
866: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
868: PetscInt nt,mbs=a->mbs,bs=A->rmap.bs;
869: PetscScalar *x,*from,zero=0.0;
870:
872: VecGetLocalSize(xx,&nt);
873: if (nt != A->cmap.n) {
874: SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");
875: }
877: /* diagonal part */
878: (*a->A->ops->mult)(a->A,xx,a->slvec1a);
879: VecSet(a->slvec1b,zero);
881: /* subdiagonal part */
882: (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);
883: CHKMEMQ;
884: /* copy x into the vec slvec0 */
885: VecGetArray(a->slvec0,&from);
886: VecGetArray(xx,&x);
887: CHKMEMQ;
888: PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
889: CHKMEMQ;
890: VecRestoreArray(a->slvec0,&from);
891:
892: CHKMEMQ;
893: VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
894: CHKMEMQ;
895: VecRestoreArray(xx,&x);
896: CHKMEMQ;
897: VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
898: CHKMEMQ;
899: /* supperdiagonal part */
900: (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);
901: CHKMEMQ;
902: return(0);
903: }
907: PetscErrorCode MatMult_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy)
908: {
909: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
911: PetscInt nt;
914: VecGetLocalSize(xx,&nt);
915: if (nt != A->cmap.n) {
916: SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");
917: }
918: VecGetLocalSize(yy,&nt);
919: if (nt != A->rmap.N) {
920: SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy");
921: }
923: VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
924: /* do diagonal part */
925: (*a->A->ops->mult)(a->A,xx,yy);
926: /* do supperdiagonal part */
927: VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
928: (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
929: /* do subdiagonal part */
930: (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
931: VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
932: VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
934: return(0);
935: }
939: PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
940: {
941: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
943: PetscInt mbs=a->mbs,bs=A->rmap.bs;
944: PetscScalar *x,*from,zero=0.0;
945:
947: /*
948: PetscSynchronizedPrintf(A->comm," MatMultAdd is called ...\n");
949: PetscSynchronizedFlush(A->comm);
950: */
951: /* diagonal part */
952: (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);
953: VecSet(a->slvec1b,zero);
955: /* subdiagonal part */
956: (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);
958: /* copy x into the vec slvec0 */
959: VecGetArray(a->slvec0,&from);
960: VecGetArray(xx,&x);
961: PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));
962: VecRestoreArray(a->slvec0,&from);
963:
964: VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
965: VecRestoreArray(xx,&x);
966: VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);
967:
968: /* supperdiagonal part */
969: (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);
970:
971: return(0);
972: }
976: PetscErrorCode MatMultAdd_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy,Vec zz)
977: {
978: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
982: VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
983: /* do diagonal part */
984: (*a->A->ops->multadd)(a->A,xx,yy,zz);
985: /* do supperdiagonal part */
986: VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
987: (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);
989: /* do subdiagonal part */
990: (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
991: VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
992: VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
994: return(0);
995: }
997: /*
998: This only works correctly for square matrices where the subblock A->A is the
999: diagonal block
1000: */
1003: PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v)
1004: {
1005: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1009: /* if (a->rmap.N != a->cmap.N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */
1010: MatGetDiagonal(a->A,v);
1011: return(0);
1012: }
1016: PetscErrorCode MatScale_MPISBAIJ(Mat A,PetscScalar aa)
1017: {
1018: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1022: MatScale(a->A,aa);
1023: MatScale(a->B,aa);
1024: return(0);
1025: }
1029: PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1030: {
1031: Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data;
1032: PetscScalar *vworkA,*vworkB,**pvA,**pvB,*v_p;
1034: PetscInt bs = matin->rmap.bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB;
1035: PetscInt nztot,nzA,nzB,lrow,brstart = matin->rmap.rstart,brend = matin->rmap.rend;
1036: PetscInt *cmap,*idx_p,cstart = mat->rstartbs;
1039: if (mat->getrowactive == PETSC_TRUE) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active");
1040: mat->getrowactive = PETSC_TRUE;
1042: if (!mat->rowvalues && (idx || v)) {
1043: /*
1044: allocate enough space to hold information from the longest row.
1045: */
1046: Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data;
1047: Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ*)mat->B->data;
1048: PetscInt max = 1,mbs = mat->mbs,tmp;
1049: for (i=0; i<mbs; i++) {
1050: tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */
1051: if (max < tmp) { max = tmp; }
1052: }
1053: PetscMalloc(max*bs2*(sizeof(PetscInt)+sizeof(PetscScalar)),&mat->rowvalues);
1054: mat->rowindices = (PetscInt*)(mat->rowvalues + max*bs2);
1055: }
1056:
1057: if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,"Only local rows")
1058: lrow = row - brstart; /* local row index */
1060: pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
1061: if (!v) {pvA = 0; pvB = 0;}
1062: if (!idx) {pcA = 0; if (!v) pcB = 0;}
1063: (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);
1064: (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);
1065: nztot = nzA + nzB;
1067: cmap = mat->garray;
1068: if (v || idx) {
1069: if (nztot) {
1070: /* Sort by increasing column numbers, assuming A and B already sorted */
1071: PetscInt imark = -1;
1072: if (v) {
1073: *v = v_p = mat->rowvalues;
1074: for (i=0; i<nzB; i++) {
1075: if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i];
1076: else break;
1077: }
1078: imark = i;
1079: for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i];
1080: for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i];
1081: }
1082: if (idx) {
1083: *idx = idx_p = mat->rowindices;
1084: if (imark > -1) {
1085: for (i=0; i<imark; i++) {
1086: idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1087: }
1088: } else {
1089: for (i=0; i<nzB; i++) {
1090: if (cmap[cworkB[i]/bs] < cstart)
1091: idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ;
1092: else break;
1093: }
1094: imark = i;
1095: }
1096: for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i];
1097: for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ;
1098: }
1099: } else {
1100: if (idx) *idx = 0;
1101: if (v) *v = 0;
1102: }
1103: }
1104: *nz = nztot;
1105: (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);
1106: (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);
1107: return(0);
1108: }
1112: PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1113: {
1114: Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
1117: if (!baij->getrowactive) {
1118: SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first");
1119: }
1120: baij->getrowactive = PETSC_FALSE;
1121: return(0);
1122: }
1126: PetscErrorCode MatGetRowUpperTriangular_MPISBAIJ(Mat A)
1127: {
1128: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1129: Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;
1132: aA->getrow_utriangular = PETSC_TRUE;
1133: return(0);
1134: }
1137: PetscErrorCode MatRestoreRowUpperTriangular_MPISBAIJ(Mat A)
1138: {
1139: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1140: Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;
1143: aA->getrow_utriangular = PETSC_FALSE;
1144: return(0);
1145: }
1149: PetscErrorCode MatRealPart_MPISBAIJ(Mat A)
1150: {
1151: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1155: MatRealPart(a->A);
1156: MatRealPart(a->B);
1157: return(0);
1158: }
1162: PetscErrorCode MatImaginaryPart_MPISBAIJ(Mat A)
1163: {
1164: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data;
1168: MatImaginaryPart(a->A);
1169: MatImaginaryPart(a->B);
1170: return(0);
1171: }
1175: PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A)
1176: {
1177: Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data;
1181: MatZeroEntries(l->A);
1182: MatZeroEntries(l->B);
1183: return(0);
1184: }
1188: PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info)
1189: {
1190: Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)matin->data;
1191: Mat A = a->A,B = a->B;
1193: PetscReal isend[5],irecv[5];
1196: info->block_size = (PetscReal)matin->rmap.bs;
1197: MatGetInfo(A,MAT_LOCAL,info);
1198: isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
1199: isend[3] = info->memory; isend[4] = info->mallocs;
1200: MatGetInfo(B,MAT_LOCAL,info);
1201: isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
1202: isend[3] += info->memory; isend[4] += info->mallocs;
1203: if (flag == MAT_LOCAL) {
1204: info->nz_used = isend[0];
1205: info->nz_allocated = isend[1];
1206: info->nz_unneeded = isend[2];
1207: info->memory = isend[3];
1208: info->mallocs = isend[4];
1209: } else if (flag == MAT_GLOBAL_MAX) {
1210: MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPI_MAX,matin->comm);
1211: info->nz_used = irecv[0];
1212: info->nz_allocated = irecv[1];