1 #ifdef PETSC_RCS_HEADER 2 static char vcid[] = "$Id: mpibaij.c,v 1.118 1998/04/15 22:50:46 curfman Exp curfman $"; 3 #endif 4 5 #include "pinclude/pviewer.h" /*I "mat.h" I*/ 6 #include "src/mat/impls/baij/mpi/mpibaij.h" 7 #include "src/vec/vecimpl.h" 8 9 10 extern int MatSetUpMultiply_MPIBAIJ(Mat); 11 extern int DisAssemble_MPIBAIJ(Mat); 12 extern int MatIncreaseOverlap_MPIBAIJ(Mat,int,IS *,int); 13 extern int MatGetSubMatrices_MPIBAIJ(Mat,int,IS *,IS *,MatGetSubMatrixCall,Mat **); 14 15 /* 16 Local utility routine that creates a mapping from the global column 17 number to the local number in the off-diagonal part of the local 18 storage of the matrix. This is done in a non scable way since the 19 length of colmap equals the global matrix length. 20 */ 21 #undef __FUNC__ 22 #define __FUNC__ "CreateColmap_MPIBAIJ_Private" 23 static int CreateColmap_MPIBAIJ_Private(Mat mat) 24 { 25 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 26 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*) baij->B->data; 27 int nbs = B->nbs,i,bs=B->bs;; 28 29 PetscFunctionBegin; 30 baij->colmap = (int *) PetscMalloc((baij->Nbs+1)*sizeof(int));CHKPTRQ(baij->colmap); 31 PLogObjectMemory(mat,baij->Nbs*sizeof(int)); 32 PetscMemzero(baij->colmap,baij->Nbs*sizeof(int)); 33 for ( i=0; i<nbs; i++ ) baij->colmap[baij->garray[i]] = i*bs+1; 34 PetscFunctionReturn(0); 35 } 36 37 #define CHUNKSIZE 10 38 39 #define MatSetValues_SeqBAIJ_A_Private(row,col,value,addv) \ 40 { \ 41 \ 42 brow = row/bs; \ 43 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 44 rmax = aimax[brow]; nrow = ailen[brow]; \ 45 bcol = col/bs; \ 46 ridx = row % bs; cidx = col % bs; \ 47 low = 0; high = nrow; \ 48 while (high-low > 3) { \ 49 t = (low+high)/2; \ 50 if (rp[t] > bcol) high = t; \ 51 else low = t; \ 52 } \ 53 for ( _i=low; _i<high; _i++ ) { \ 54 if (rp[_i] > bcol) break; \ 55 if (rp[_i] == bcol) { \ 56 bap = ap + bs2*_i + bs*cidx + ridx; \ 57 if (addv == ADD_VALUES) *bap += value; \ 58 else *bap = value; \ 59 goto a_noinsert; \ 60 } \ 61 } \ 62 if (a->nonew == 1) goto a_noinsert; \ 63 else if (a->nonew == -1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Inserting a new nonzero into matrix"); \ 64 if (nrow >= rmax) { \ 65 /* there is no extra room in row, therefore enlarge */ \ 66 int new_nz = ai[a->mbs] + CHUNKSIZE,len,*new_i,*new_j; \ 67 Scalar *new_a; \ 68 \ 69 if (a->nonew == -2) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Inserting a new nonzero in the matrix"); \ 70 \ 71 /* malloc new storage space */ \ 72 len = new_nz*(sizeof(int)+bs2*sizeof(Scalar))+(a->mbs+1)*sizeof(int); \ 73 new_a = (Scalar *) PetscMalloc( len ); CHKPTRQ(new_a); \ 74 new_j = (int *) (new_a + bs2*new_nz); \ 75 new_i = new_j + new_nz; \ 76 \ 77 /* copy over old data into new slots */ \ 78 for ( ii=0; ii<brow+1; ii++ ) {new_i[ii] = ai[ii];} \ 79 for ( ii=brow+1; ii<a->mbs+1; ii++ ) {new_i[ii] = ai[ii]+CHUNKSIZE;} \ 80 PetscMemcpy(new_j,aj,(ai[brow]+nrow)*sizeof(int)); \ 81 len = (new_nz - CHUNKSIZE - ai[brow] - nrow); \ 82 PetscMemcpy(new_j+ai[brow]+nrow+CHUNKSIZE,aj+ai[brow]+nrow, \ 83 len*sizeof(int)); \ 84 PetscMemcpy(new_a,aa,(ai[brow]+nrow)*bs2*sizeof(Scalar)); \ 85 PetscMemzero(new_a+bs2*(ai[brow]+nrow),bs2*CHUNKSIZE*sizeof(Scalar)); \ 86 PetscMemcpy(new_a+bs2*(ai[brow]+nrow+CHUNKSIZE), \ 87 aa+bs2*(ai[brow]+nrow),bs2*len*sizeof(Scalar)); \ 88 /* free up old matrix storage */ \ 89 PetscFree(a->a); \ 90 if (!a->singlemalloc) {PetscFree(a->i);PetscFree(a->j);} \ 91 aa = a->a = new_a; ai = a->i = new_i; aj = a->j = new_j; \ 92 a->singlemalloc = 1; \ 93 \ 94 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 95 rmax = aimax[brow] = aimax[brow] + CHUNKSIZE; \ 96 PLogObjectMemory(A,CHUNKSIZE*(sizeof(int) + bs2*sizeof(Scalar))); \ 97 a->maxnz += bs2*CHUNKSIZE; \ 98 a->reallocs++; \ 99 a->nz++; \ 100 } \ 101 N = nrow++ - 1; \ 102 /* shift up all the later entries in this row */ \ 103 for ( ii=N; ii>=_i; ii-- ) { \ 104 rp[ii+1] = rp[ii]; \ 105 PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(Scalar)); \ 106 } \ 107 if (N>=_i) PetscMemzero(ap+bs2*_i,bs2*sizeof(Scalar)); \ 108 rp[_i] = bcol; \ 109 ap[bs2*_i + bs*cidx + ridx] = value; \ 110 a_noinsert:; \ 111 ailen[brow] = nrow; \ 112 } 113 114 #define MatSetValues_SeqBAIJ_B_Private(row,col,value,addv) \ 115 { \ 116 \ 117 brow = row/bs; \ 118 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 119 rmax = bimax[brow]; nrow = bilen[brow]; \ 120 bcol = col/bs; \ 121 ridx = row % bs; cidx = col % bs; \ 122 low = 0; high = nrow; \ 123 while (high-low > 3) { \ 124 t = (low+high)/2; \ 125 if (rp[t] > bcol) high = t; \ 126 else low = t; \ 127 } \ 128 for ( _i=low; _i<high; _i++ ) { \ 129 if (rp[_i] > bcol) break; \ 130 if (rp[_i] == bcol) { \ 131 bap = ap + bs2*_i + bs*cidx + ridx; \ 132 if (addv == ADD_VALUES) *bap += value; \ 133 else *bap = value; \ 134 goto b_noinsert; \ 135 } \ 136 } \ 137 if (b->nonew == 1) goto b_noinsert; \ 138 else if (b->nonew == -1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Inserting a new nonzero into matrix"); \ 139 if (nrow >= rmax) { \ 140 /* there is no extra room in row, therefore enlarge */ \ 141 int new_nz = bi[b->mbs] + CHUNKSIZE,len,*new_i,*new_j; \ 142 Scalar *new_a; \ 143 \ 144 if (b->nonew == -2) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Inserting a new nonzero in the matrix"); \ 145 \ 146 /* malloc new storage space */ \ 147 len = new_nz*(sizeof(int)+bs2*sizeof(Scalar))+(b->mbs+1)*sizeof(int); \ 148 new_a = (Scalar *) PetscMalloc( len ); CHKPTRQ(new_a); \ 149 new_j = (int *) (new_a + bs2*new_nz); \ 150 new_i = new_j + new_nz; \ 151 \ 152 /* copy over old data into new slots */ \ 153 for ( ii=0; ii<brow+1; ii++ ) {new_i[ii] = bi[ii];} \ 154 for ( ii=brow+1; ii<b->mbs+1; ii++ ) {new_i[ii] = bi[ii]+CHUNKSIZE;} \ 155 PetscMemcpy(new_j,bj,(bi[brow]+nrow)*sizeof(int)); \ 156 len = (new_nz - CHUNKSIZE - bi[brow] - nrow); \ 157 PetscMemcpy(new_j+bi[brow]+nrow+CHUNKSIZE,bj+bi[brow]+nrow, \ 158 len*sizeof(int)); \ 159 PetscMemcpy(new_a,ba,(bi[brow]+nrow)*bs2*sizeof(Scalar)); \ 160 PetscMemzero(new_a+bs2*(bi[brow]+nrow),bs2*CHUNKSIZE*sizeof(Scalar)); \ 161 PetscMemcpy(new_a+bs2*(bi[brow]+nrow+CHUNKSIZE), \ 162 ba+bs2*(bi[brow]+nrow),bs2*len*sizeof(Scalar)); \ 163 /* free up old matrix storage */ \ 164 PetscFree(b->a); \ 165 if (!b->singlemalloc) {PetscFree(b->i);PetscFree(b->j);} \ 166 ba = b->a = new_a; bi = b->i = new_i; bj = b->j = new_j; \ 167 b->singlemalloc = 1; \ 168 \ 169 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 170 rmax = bimax[brow] = bimax[brow] + CHUNKSIZE; \ 171 PLogObjectMemory(B,CHUNKSIZE*(sizeof(int) + bs2*sizeof(Scalar))); \ 172 b->maxnz += bs2*CHUNKSIZE; \ 173 b->reallocs++; \ 174 b->nz++; \ 175 } \ 176 N = nrow++ - 1; \ 177 /* shift up all the later entries in this row */ \ 178 for ( ii=N; ii>=_i; ii-- ) { \ 179 rp[ii+1] = rp[ii]; \ 180 PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(Scalar)); \ 181 } \ 182 if (N>=_i) PetscMemzero(ap+bs2*_i,bs2*sizeof(Scalar)); \ 183 rp[_i] = bcol; \ 184 ap[bs2*_i + bs*cidx + ridx] = value; \ 185 b_noinsert:; \ 186 bilen[brow] = nrow; \ 187 } 188 189 #undef __FUNC__ 190 #define __FUNC__ "MatSetValues_MPIBAIJ" 191 int MatSetValues_MPIBAIJ(Mat mat,int m,int *im,int n,int *in,Scalar *v,InsertMode addv) 192 { 193 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 194 Scalar value; 195 int ierr,i,j,row,col; 196 int roworiented = baij->roworiented,rstart_orig=baij->rstart_bs ; 197 int rend_orig=baij->rend_bs,cstart_orig=baij->cstart_bs; 198 int cend_orig=baij->cend_bs,bs=baij->bs; 199 200 /* Some Variables required in the macro */ 201 Mat A = baij->A; 202 Mat_SeqBAIJ *a = (Mat_SeqBAIJ *) (A)->data; 203 int *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 204 Scalar *aa=a->a; 205 206 Mat B = baij->B; 207 Mat_SeqBAIJ *b = (Mat_SeqBAIJ *) (B)->data; 208 int *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 209 Scalar *ba=b->a; 210 211 int *rp,ii,nrow,_i,rmax,N,brow,bcol; 212 int low,high,t,ridx,cidx,bs2=a->bs2; 213 Scalar *ap,*bap; 214 215 PetscFunctionBegin; 216 for ( i=0; i<m; i++ ) { 217 #if defined(USE_PETSC_BOPT_g) 218 if (im[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Negative row"); 219 if (im[i] >= baij->M) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Row too large"); 220 #endif 221 if (im[i] >= rstart_orig && im[i] < rend_orig) { 222 row = im[i] - rstart_orig; 223 for ( j=0; j<n; j++ ) { 224 if (in[j] >= cstart_orig && in[j] < cend_orig){ 225 col = in[j] - cstart_orig; 226 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 227 MatSetValues_SeqBAIJ_A_Private(row,col,value,addv); 228 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 229 } 230 #if defined(USE_PETSC_BOPT_g) 231 else if (in[j] < 0) {SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Negative column");} 232 else if (in[j] >= baij->N) {SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Col too large");} 233 #endif 234 else { 235 if (mat->was_assembled) { 236 if (!baij->colmap) { 237 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 238 } 239 col = baij->colmap[in[j]/bs] - 1 + in[j]%bs; 240 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 241 ierr = DisAssemble_MPIBAIJ(mat); CHKERRQ(ierr); 242 col = in[j]; 243 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 244 B = baij->B; 245 b = (Mat_SeqBAIJ *) (B)->data; 246 bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 247 ba=b->a; 248 } 249 } else col = in[j]; 250 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 251 MatSetValues_SeqBAIJ_B_Private(row,col,value,addv); 252 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 253 } 254 } 255 } else { 256 if (roworiented && !baij->donotstash) { 257 ierr = StashValues_Private(&baij->stash,im[i],n,in,v+i*n,addv);CHKERRQ(ierr); 258 } else { 259 if (!baij->donotstash) { 260 row = im[i]; 261 for ( j=0; j<n; j++ ) { 262 ierr = StashValues_Private(&baij->stash,row,1,in+j,v+i+j*m,addv);CHKERRQ(ierr); 263 } 264 } 265 } 266 } 267 } 268 PetscFunctionReturn(0); 269 } 270 271 extern int MatSetValuesBlocked_SeqBAIJ(Mat,int,int*,int,int*,Scalar*,InsertMode); 272 #undef __FUNC__ 273 #define __FUNC__ "MatSetValuesBlocked_MPIBAIJ" 274 int MatSetValuesBlocked_MPIBAIJ(Mat mat,int m,int *im,int n,int *in,Scalar *v,InsertMode addv) 275 { 276 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 277 Scalar *value,*barray=baij->barray; 278 int ierr,i,j,ii,jj,row,col,k,l; 279 int roworiented = baij->roworiented,rstart=baij->rstart ; 280 int rend=baij->rend,cstart=baij->cstart,stepval; 281 int cend=baij->cend,bs=baij->bs,bs2=baij->bs2; 282 283 if(!barray) { 284 baij->barray = barray = (Scalar*) PetscMalloc(bs2*sizeof(Scalar)); CHKPTRQ(barray); 285 } 286 287 if (roworiented) { 288 stepval = (n-1)*bs; 289 } else { 290 stepval = (m-1)*bs; 291 } 292 for ( i=0; i<m; i++ ) { 293 #if defined(USE_PETSC_BOPT_g) 294 if (im[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Negative row"); 295 if (im[i] >= baij->Mbs) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Row too large"); 296 #endif 297 if (im[i] >= rstart && im[i] < rend) { 298 row = im[i] - rstart; 299 for ( j=0; j<n; j++ ) { 300 /* If NumCol = 1 then a copy is not required */ 301 if ((roworiented) && (n == 1)) { 302 barray = v + i*bs2; 303 } else if((!roworiented) && (m == 1)) { 304 barray = v + j*bs2; 305 } else { /* Here a copy is required */ 306 if (roworiented) { 307 value = v + i*(stepval+bs)*bs + j*bs; 308 } else { 309 value = v + j*(stepval+bs)*bs + i*bs; 310 } 311 for ( ii=0; ii<bs; ii++,value+=stepval ) { 312 for (jj=0; jj<bs; jj++ ) { 313 *barray++ = *value++; 314 } 315 } 316 barray -=bs2; 317 } 318 319 if (in[j] >= cstart && in[j] < cend){ 320 col = in[j] - cstart; 321 ierr = MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 322 } 323 #if defined(USE_PETSC_BOPT_g) 324 else if (in[j] < 0) {SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Negative column");} 325 else if (in[j] >= baij->Nbs) {SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Column too large");} 326 #endif 327 else { 328 if (mat->was_assembled) { 329 if (!baij->colmap) { 330 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 331 } 332 333 #if defined(USE_PETSC_BOPT_g) 334 if ((baij->colmap[in[j]] - 1) % bs) {SETERRQ(PETSC_ERR_PLIB,0,"Incorrect colmap");} 335 #endif 336 col = (baij->colmap[in[j]] - 1)/bs; 337 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 338 ierr = DisAssemble_MPIBAIJ(mat); CHKERRQ(ierr); 339 col = in[j]; 340 } 341 } 342 else col = in[j]; 343 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 344 } 345 } 346 } else { 347 if (!baij->donotstash) { 348 if (roworiented ) { 349 row = im[i]*bs; 350 value = v + i*(stepval+bs)*bs; 351 for ( j=0; j<bs; j++,row++ ) { 352 for ( k=0; k<n; k++ ) { 353 for ( col=in[k]*bs,l=0; l<bs; l++,col++) { 354 ierr = StashValues_Private(&baij->stash,row,1,&col,value++,addv);CHKERRQ(ierr); 355 } 356 } 357 } 358 } else { 359 for ( j=0; j<n; j++ ) { 360 value = v + j*(stepval+bs)*bs + i*bs; 361 col = in[j]*bs; 362 for ( k=0; k<bs; k++,col++,value+=stepval) { 363 for ( row = im[i]*bs,l=0; l<bs; l++,row++) { 364 ierr = StashValues_Private(&baij->stash,row,1,&col,value++,addv);CHKERRQ(ierr); 365 } 366 } 367 } 368 } 369 } 370 } 371 } 372 PetscFunctionReturn(0); 373 } 374 #include <math.h> 375 #define HASH_KEY 0.6180339887 376 /* #define HASH1(size,key) ((int)((size)*fmod(((key)*HASH_KEY),1))) */ 377 #define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(int)((size)*(tmp-(int)tmp))) 378 /* #define HASH(size,key,tmp) ((int)((size)*fmod(((key)*HASH_KEY),1))) */ 379 #undef __FUNC__ 380 #define __FUNC__ "MatSetValues_MPIBAIJ_HT" 381 int MatSetValues_MPIBAIJ_HT(Mat mat,int m,int *im,int n,int *in,Scalar *v,InsertMode addv) 382 { 383 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 384 int ierr,i,j,row,col; 385 int roworiented = baij->roworiented,rstart_orig=baij->rstart_bs ; 386 int rend_orig=baij->rend_bs,Nbs=baij->Nbs; 387 int h1,key,size=baij->ht_size,bs=baij->bs,*HT=baij->ht,idx; 388 double tmp; 389 Scalar ** HD = baij->hd,value; 390 #if defined(USE_PETSC_BOPT_g) 391 int total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 392 #endif 393 394 PetscFunctionBegin; 395 396 for ( i=0; i<m; i++ ) { 397 #if defined(USE_PETSC_BOPT_g) 398 if (im[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Negative row"); 399 if (im[i] >= baij->M) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Row too large"); 400 #endif 401 row = im[i]; 402 if (row >= rstart_orig && row < rend_orig) { 403 for ( j=0; j<n; j++ ) { 404 col = in[j]; 405 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 406 /* Look up into the Hash Table */ 407 key = (row/bs)*Nbs+(col/bs)+1; 408 h1 = HASH(size,key,tmp); 409 410 411 idx = h1; 412 #if defined(USE_PETSC_BOPT_g) 413 insert_ct++; 414 total_ct++; 415 if (HT[idx] != key) { 416 for ( idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++); 417 if (idx == size) { 418 for ( idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++); 419 if (idx == h1) { 420 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"(row,col) has no entry in the hash table"); 421 } 422 } 423 } 424 #else 425 if (HT[idx] != key) { 426 for ( idx=h1; (idx<size) && (HT[idx]!=key); idx++); 427 if (idx == size) { 428 for ( idx=0; (idx<h1) && (HT[idx]!=key); idx++); 429 if (idx == h1) { 430 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"(row,col) has no entry in the hash table"); 431 } 432 } 433 } 434 #endif 435 /* A HASH table entry is found, so insert the values at the correct address */ 436 if (addv == ADD_VALUES) *(HD[idx]+ (col % bs)*bs + (row % bs)) += value; 437 else *(HD[idx]+ (col % bs)*bs + (row % bs)) = value; 438 } 439 } else { 440 if (roworiented && !baij->donotstash) { 441 ierr = StashValues_Private(&baij->stash,im[i],n,in,v+i*n,addv);CHKERRQ(ierr); 442 } else { 443 if (!baij->donotstash) { 444 row = im[i]; 445 for ( j=0; j<n; j++ ) { 446 ierr = StashValues_Private(&baij->stash,row,1,in+j,v+i+j*m,addv);CHKERRQ(ierr); 447 } 448 } 449 } 450 } 451 } 452 #if defined(USE_PETSC_BOPT_g) 453 baij->ht_total_ct = total_ct; 454 baij->ht_insert_ct = insert_ct; 455 #endif 456 PetscFunctionReturn(0); 457 } 458 459 #undef __FUNC__ 460 #define __FUNC__ "MatSetValuesBlocked_MPIBAIJ_HT" 461 int MatSetValuesBlocked_MPIBAIJ_HT(Mat mat,int m,int *im,int n,int *in,Scalar *v,InsertMode addv) 462 { 463 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 464 int ierr,i,j,ii,jj,row,col,k,l; 465 int roworiented = baij->roworiented,rstart=baij->rstart ; 466 int rend=baij->rend,stepval,bs=baij->bs,bs2=baij->bs2; 467 int h1,key,size=baij->ht_size,idx,*HT=baij->ht,Nbs=baij->Nbs; 468 double tmp; 469 Scalar ** HD = baij->hd,*value,*v_t,*baij_a; 470 #if defined(USE_PETSC_BOPT_g) 471 int total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 472 #endif 473 474 PetscFunctionBegin; 475 476 if (roworiented) { 477 stepval = (n-1)*bs; 478 } else { 479 stepval = (m-1)*bs; 480 } 481 for ( i=0; i<m; i++ ) { 482 #if defined(USE_PETSC_BOPT_g) 483 if (im[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Negative row"); 484 if (im[i] >= baij->Mbs) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Row too large"); 485 #endif 486 row = im[i]; 487 v_t = v + i*bs2; 488 if (row >= rstart && row < rend) { 489 for ( j=0; j<n; j++ ) { 490 col = in[j]; 491 492 /* Look up into the Hash Table */ 493 key = row*Nbs+col+1; 494 h1 = HASH(size,key,tmp); 495 496 idx = h1; 497 #if defined(USE_PETSC_BOPT_g) 498 total_ct++; 499 insert_ct++; 500 if (HT[idx] != key) { 501 for ( idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++); 502 if (idx == size) { 503 for ( idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++); 504 if (idx == h1) { 505 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"(row,col) has no entry in the hash table"); 506 } 507 } 508 } 509 #else 510 if (HT[idx] != key) { 511 for ( idx=h1; (idx<size) && (HT[idx]!=key); idx++); 512 if (idx == size) { 513 for ( idx=0; (idx<h1) && (HT[idx]!=key); idx++); 514 if (idx == h1) { 515 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"(row,col) has no entry in the hash table"); 516 } 517 } 518 } 519 #endif 520 baij_a = HD[idx]; 521 if (roworiented) { 522 /*value = v + i*(stepval+bs)*bs + j*bs;*/ 523 /* value = v + (i*(stepval+bs)+j)*bs; */ 524 value = v_t; 525 v_t += bs; 526 if (addv == ADD_VALUES) { 527 for ( ii=0; ii<bs; ii++,value+=stepval) { 528 for ( jj=ii; jj<bs2; jj+=bs ) { 529 baij_a[jj] += *value++; 530 } 531 } 532 } else { 533 for ( ii=0; ii<bs; ii++,value+=stepval) { 534 for ( jj=ii; jj<bs2; jj+=bs ) { 535 baij_a[jj] = *value++; 536 } 537 } 538 } 539 } else { 540 value = v + j*(stepval+bs)*bs + i*bs; 541 if (addv == ADD_VALUES) { 542 for ( ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs ) { 543 for ( jj=0; jj<bs; jj++ ) { 544 baij_a[jj] += *value++; 545 } 546 } 547 } else { 548 for ( ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs ) { 549 for ( jj=0; jj<bs; jj++ ) { 550 baij_a[jj] = *value++; 551 } 552 } 553 } 554 } 555 } 556 } else { 557 if (!baij->donotstash) { 558 if (roworiented ) { 559 row = im[i]*bs; 560 value = v + i*(stepval+bs)*bs; 561 for ( j=0; j<bs; j++,row++ ) { 562 for ( k=0; k<n; k++ ) { 563 for ( col=in[k]*bs,l=0; l<bs; l++,col++) { 564 ierr = StashValues_Private(&baij->stash,row,1,&col,value++,addv);CHKERRQ(ierr); 565 } 566 } 567 } 568 } else { 569 for ( j=0; j<n; j++ ) { 570 value = v + j*(stepval+bs)*bs + i*bs; 571 col = in[j]*bs; 572 for ( k=0; k<bs; k++,col++,value+=stepval) { 573 for ( row = im[i]*bs,l=0; l<bs; l++,row++) { 574 ierr = StashValues_Private(&baij->stash,row,1,&col,value++,addv);CHKERRQ(ierr); 575 } 576 } 577 } 578 } 579 } 580 } 581 } 582 #if defined(USE_PETSC_BOPT_g) 583 baij->ht_total_ct = total_ct; 584 baij->ht_insert_ct = insert_ct; 585 #endif 586 PetscFunctionReturn(0); 587 } 588 589 #undef __FUNC__ 590 #define __FUNC__ "MatGetValues_MPIBAIJ" 591 int MatGetValues_MPIBAIJ(Mat mat,int m,int *idxm,int n,int *idxn,Scalar *v) 592 { 593 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 594 int bs=baij->bs,ierr,i,j, bsrstart = baij->rstart*bs, bsrend = baij->rend*bs; 595 int bscstart = baij->cstart*bs, bscend = baij->cend*bs,row,col; 596 597 PetscFunctionBegin; 598 for ( i=0; i<m; i++ ) { 599 if (idxm[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Negative row"); 600 if (idxm[i] >= baij->M) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Row too large"); 601 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 602 row = idxm[i] - bsrstart; 603 for ( j=0; j<n; j++ ) { 604 if (idxn[j] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Negative column"); 605 if (idxn[j] >= baij->N) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Column too large"); 606 if (idxn[j] >= bscstart && idxn[j] < bscend){ 607 col = idxn[j] - bscstart; 608 ierr = MatGetValues(baij->A,1,&row,1,&col,v+i*n+j); CHKERRQ(ierr); 609 } else { 610 if (!baij->colmap) { 611 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 612 } 613 if((baij->colmap[idxn[j]/bs]-1 < 0) || 614 (baij->garray[(baij->colmap[idxn[j]/bs]-1)/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 615 else { 616 col = (baij->colmap[idxn[j]/bs]-1) + idxn[j]%bs; 617 ierr = MatGetValues(baij->B,1,&row,1,&col,v+i*n+j); CHKERRQ(ierr); 618 } 619 } 620 } 621 } else { 622 SETERRQ(PETSC_ERR_SUP,0,"Only local values currently supported"); 623 } 624 } 625 PetscFunctionReturn(0); 626 } 627 628 #undef __FUNC__ 629 #define __FUNC__ "MatNorm_MPIBAIJ" 630 int MatNorm_MPIBAIJ(Mat mat,NormType type,double *norm) 631 { 632 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 633 Mat_SeqBAIJ *amat = (Mat_SeqBAIJ*) baij->A->data, *bmat = (Mat_SeqBAIJ*) baij->B->data; 634 int ierr, i,bs2=baij->bs2; 635 double sum = 0.0; 636 Scalar *v; 637 638 PetscFunctionBegin; 639 if (baij->size == 1) { 640 ierr = MatNorm(baij->A,type,norm); CHKERRQ(ierr); 641 } else { 642 if (type == NORM_FROBENIUS) { 643 v = amat->a; 644 for (i=0; i<amat->nz*bs2; i++ ) { 645 #if defined(USE_PETSC_COMPLEX) 646 sum += real(conj(*v)*(*v)); v++; 647 #else 648 sum += (*v)*(*v); v++; 649 #endif 650 } 651 v = bmat->a; 652 for (i=0; i<bmat->nz*bs2; i++ ) { 653 #if defined(USE_PETSC_COMPLEX) 654 sum += real(conj(*v)*(*v)); v++; 655 #else 656 sum += (*v)*(*v); v++; 657 #endif 658 } 659 ierr = MPI_Allreduce(&sum,norm,1,MPI_DOUBLE,MPI_SUM,mat->comm);CHKERRQ(ierr); 660 *norm = sqrt(*norm); 661 } else { 662 SETERRQ(PETSC_ERR_SUP,0,"No support for this norm yet"); 663 } 664 } 665 PetscFunctionReturn(0); 666 } 667 668 #undef __FUNC__ 669 #define __FUNC__ "MatAssemblyBegin_MPIBAIJ" 670 int MatAssemblyBegin_MPIBAIJ(Mat mat,MatAssemblyType mode) 671 { 672 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 673 MPI_Comm comm = mat->comm; 674 int size = baij->size, *owners = baij->rowners,bs=baij->bs; 675 int rank = baij->rank,tag = mat->tag, *owner,*starts,count,ierr; 676 MPI_Request *send_waits,*recv_waits; 677 int *nprocs,i,j,idx,*procs,nsends,nreceives,nmax,*work; 678 InsertMode addv; 679 Scalar *rvalues,*svalues; 680 681 PetscFunctionBegin; 682 /* make sure all processors are either in INSERTMODE or ADDMODE */ 683 ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,comm);CHKERRQ(ierr); 684 if (addv == (ADD_VALUES|INSERT_VALUES)) { 685 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Some processors inserted others added"); 686 } 687 mat->insertmode = addv; /* in case this processor had no cache */ 688 689 /* first count number of contributors to each processor */ 690 nprocs = (int *) PetscMalloc( 2*size*sizeof(int) ); CHKPTRQ(nprocs); 691 PetscMemzero(nprocs,2*size*sizeof(int)); procs = nprocs + size; 692 owner = (int *) PetscMalloc( (baij->stash.n+1)*sizeof(int) ); CHKPTRQ(owner); 693 for ( i=0; i<baij->stash.n; i++ ) { 694 idx = baij->stash.idx[i]; 695 for ( j=0; j<size; j++ ) { 696 if (idx >= owners[j]*bs && idx < owners[j+1]*bs) { 697 nprocs[j]++; procs[j] = 1; owner[i] = j; break; 698 } 699 } 700 } 701 nsends = 0; for ( i=0; i<size; i++ ) { nsends += procs[i];} 702 703 /* inform other processors of number of messages and max length*/ 704 work = (int *) PetscMalloc( size*sizeof(int) ); CHKPTRQ(work); 705 ierr = MPI_Allreduce(procs, work,size,MPI_INT,MPI_SUM,comm);CHKERRQ(ierr); 706 nreceives = work[rank]; 707 ierr = MPI_Allreduce( nprocs, work,size,MPI_INT,MPI_MAX,comm);CHKERRQ(ierr); 708 nmax = work[rank]; 709 PetscFree(work); 710 711 /* post receives: 712 1) each message will consist of ordered pairs 713 (global index,value) we store the global index as a double 714 to simplify the message passing. 715 2) since we don't know how long each individual message is we 716 allocate the largest needed buffer for each receive. Potentially 717 this is a lot of wasted space. 718 719 720 This could be done better. 721 */ 722 rvalues = (Scalar *) PetscMalloc(3*(nreceives+1)*(nmax+1)*sizeof(Scalar));CHKPTRQ(rvalues); 723 recv_waits = (MPI_Request *) PetscMalloc((nreceives+1)*sizeof(MPI_Request));CHKPTRQ(recv_waits); 724 for ( i=0; i<nreceives; i++ ) { 725 ierr = MPI_Irecv(rvalues+3*nmax*i,3*nmax,MPIU_SCALAR,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 726 } 727 728 /* do sends: 729 1) starts[i] gives the starting index in svalues for stuff going to 730 the ith processor 731 */ 732 svalues = (Scalar *) PetscMalloc(3*(baij->stash.n+1)*sizeof(Scalar));CHKPTRQ(svalues); 733 send_waits = (MPI_Request *) PetscMalloc((nsends+1)*sizeof(MPI_Request));CHKPTRQ(send_waits); 734 starts = (int *) PetscMalloc( size*sizeof(int) ); CHKPTRQ(starts); 735 starts[0] = 0; 736 for ( i=1; i<size; i++ ) { starts[i] = starts[i-1] + nprocs[i-1];} 737 for ( i=0; i<baij->stash.n; i++ ) { 738 svalues[3*starts[owner[i]]] = (Scalar) baij->stash.idx[i]; 739 svalues[3*starts[owner[i]]+1] = (Scalar) baij->stash.idy[i]; 740 svalues[3*(starts[owner[i]]++)+2] = baij->stash.array[i]; 741 } 742 PetscFree(owner); 743 starts[0] = 0; 744 for ( i=1; i<size; i++ ) { starts[i] = starts[i-1] + nprocs[i-1];} 745 count = 0; 746 for ( i=0; i<size; i++ ) { 747 if (procs[i]) { 748 ierr = MPI_Isend(svalues+3*starts[i],3*nprocs[i],MPIU_SCALAR,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 749 } 750 } 751 PetscFree(starts); PetscFree(nprocs); 752 753 /* Free cache space */ 754 PLogInfo(0,"MatAssemblyBegin_MPIBAIJ:Number of off-processor values %d\n",baij->stash.n); 755 ierr = StashDestroy_Private(&baij->stash); CHKERRQ(ierr); 756 757 baij->svalues = svalues; baij->rvalues = rvalues; 758 baij->nsends = nsends; baij->nrecvs = nreceives; 759 baij->send_waits = send_waits; baij->recv_waits = recv_waits; 760 baij->rmax = nmax; 761 762 PetscFunctionReturn(0); 763 } 764 765 /* 766 Creates the hash table, and sets the table 767 This table is created only once. 768 If new entried need to be added to the matrix 769 then the hash table has to be destroyed and 770 recreated. 771 */ 772 #undef __FUNC__ 773 #define __FUNC__ "MatCreateHashTable_MPIBAIJ_Private" 774 int MatCreateHashTable_MPIBAIJ_Private(Mat mat,double factor) 775 { 776 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 777 Mat A = baij->A, B=baij->B; 778 Mat_SeqBAIJ *a=(Mat_SeqBAIJ *)A->data, *b=(Mat_SeqBAIJ *)B->data; 779 int i,j,k,nz=a->nz+b->nz,h1,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 780 int size,bs2=baij->bs2,rstart=baij->rstart; 781 int cstart=baij->cstart,*garray=baij->garray,row,col,Nbs=baij->Nbs; 782 int *HT,key; 783 Scalar **HD; 784 double tmp; 785 #if defined(USE_PETSC_BOPT_g) 786 int ct=0,max=0; 787 #endif 788 789 PetscFunctionBegin; 790 baij->ht_size=(int)(factor*nz); 791 size = baij->ht_size; 792 793 if (baij->ht) { 794 PetscFunctionReturn(0); 795 } 796 797 /* Allocate Memory for Hash Table */ 798 baij->hd = (Scalar**)PetscMalloc((size)*(sizeof(int)+sizeof(Scalar*))+1); CHKPTRQ(baij->hd); 799 baij->ht = (int*)(baij->hd + size); 800 HD = baij->hd; 801 HT = baij->ht; 802 803 804 PetscMemzero(HD,size*(sizeof(int)+sizeof(Scalar*))); 805 806 807 /* Loop Over A */ 808 for ( i=0; i<a->mbs; i++ ) { 809 for ( j=ai[i]; j<ai[i+1]; j++ ) { 810 row = i+rstart; 811 col = aj[j]+cstart; 812 813 key = row*Nbs + col + 1; 814 h1 = HASH(size,key,tmp); 815 for ( k=0; k<size; k++ ){ 816 if (HT[(h1+k)%size] == 0.0) { 817 HT[(h1+k)%size] = key; 818 HD[(h1+k)%size] = a->a + j*bs2; 819 break; 820 #if defined(USE_PETSC_BOPT_g) 821 } else { 822 ct++; 823 #endif 824 } 825 } 826 #if defined(USE_PETSC_BOPT_g) 827 if (k> max) max = k; 828 #endif 829 } 830 } 831 /* Loop Over B */ 832 for ( i=0; i<b->mbs; i++ ) { 833 for ( j=bi[i]; j<bi[i+1]; j++ ) { 834 row = i+rstart; 835 col = garray[bj[j]]; 836 key = row*Nbs + col + 1; 837 h1 = HASH(size,key,tmp); 838 for ( k=0; k<size; k++ ){ 839 if (HT[(h1+k)%size] == 0.0) { 840 HT[(h1+k)%size] = key; 841 HD[(h1+k)%size] = b->a + j*bs2; 842 break; 843 #if defined(USE_PETSC_BOPT_g) 844 } else { 845 ct++; 846 #endif 847 } 848 } 849 #if defined(USE_PETSC_BOPT_g) 850 if (k> max) max = k; 851 #endif 852 } 853 } 854 855 /* Print Summary */ 856 #if defined(USE_PETSC_BOPT_g) 857 for ( i=0,j=0; i<size; i++) 858 if (HT[i]) {j++;} 859 PLogInfo(0,"MatCreateHashTable_MPIBAIJ_Private: Average Search = %5.2f,max search = %d\n", 860 (j== 0)? 0.0:((double)(ct+j))/j,max); 861 #endif 862 PetscFunctionReturn(0); 863 } 864 865 #undef __FUNC__ 866 #define __FUNC__ "MatAssemblyEnd_MPIBAIJ" 867 int MatAssemblyEnd_MPIBAIJ(Mat mat,MatAssemblyType mode) 868 { 869 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 870 MPI_Status *send_status,recv_status; 871 int imdex,nrecvs = baij->nrecvs, count = nrecvs, i, n, ierr; 872 int bs=baij->bs,row,col,other_disassembled; 873 Scalar *values,val; 874 InsertMode addv = mat->insertmode; 875 876 PetscFunctionBegin; 877 /* wait on receives */ 878 while (count) { 879 ierr = MPI_Waitany(nrecvs,baij->recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 880 /* unpack receives into our local space */ 881 values = baij->rvalues + 3*imdex*baij->rmax; 882 ierr = MPI_Get_count(&recv_status,MPIU_SCALAR,&n);CHKERRQ(ierr); 883 n = n/3; 884 for ( i=0; i<n; i++ ) { 885 row = (int) PetscReal(values[3*i]) - baij->rstart*bs; 886 col = (int) PetscReal(values[3*i+1]); 887 val = values[3*i+2]; 888 if (col >= baij->cstart*bs && col < baij->cend*bs) { 889 col -= baij->cstart*bs; 890 ierr = MatSetValues(baij->A,1,&row,1,&col,&val,addv); CHKERRQ(ierr) 891 } else { 892 if (mat->was_assembled) { 893 if (!baij->colmap) { 894 ierr = CreateColmap_MPIBAIJ_Private(mat); CHKERRQ(ierr); 895 } 896 col = (baij->colmap[col/bs]) - 1 + col%bs; 897 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 898 ierr = DisAssemble_MPIBAIJ(mat); CHKERRQ(ierr); 899 col = (int) PetscReal(values[3*i+1]); 900 } 901 } 902 ierr = MatSetValues(baij->B,1,&row,1,&col,&val,addv); CHKERRQ(ierr) 903 } 904 } 905 count--; 906 } 907 PetscFree(baij->recv_waits); PetscFree(baij->rvalues); 908 909 /* wait on sends */ 910 if (baij->nsends) { 911 send_status = (MPI_Status *) PetscMalloc(baij->nsends*sizeof(MPI_Status));CHKPTRQ(send_status); 912 ierr = MPI_Waitall(baij->nsends,baij->send_waits,send_status);CHKERRQ(ierr); 913 PetscFree(send_status); 914 } 915 PetscFree(baij->send_waits); PetscFree(baij->svalues); 916 917 ierr = MatAssemblyBegin(baij->A,mode); CHKERRQ(ierr); 918 ierr = MatAssemblyEnd(baij->A,mode); CHKERRQ(ierr); 919 920 /* determine if any processor has disassembled, if so we must 921 also disassemble ourselfs, in order that we may reassemble. */ 922 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,mat->comm);CHKERRQ(ierr); 923 if (mat->was_assembled && !other_disassembled) { 924 ierr = DisAssemble_MPIBAIJ(mat); CHKERRQ(ierr); 925 } 926 927 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 928 ierr = MatSetUpMultiply_MPIBAIJ(mat); CHKERRQ(ierr); 929 } 930 ierr = MatAssemblyBegin(baij->B,mode); CHKERRQ(ierr); 931 ierr = MatAssemblyEnd(baij->B,mode); CHKERRQ(ierr); 932 933 #if defined(USE_PETSC_BOPT_g) 934 if (baij->ht && mode== MAT_FINAL_ASSEMBLY) { 935 PLogInfo(0,"MatAssemblyEnd_MPIBAIJ:Average Hash Table Search in MatSetValues = %5.2f\n", 936 ((double)baij->ht_total_ct)/baij->ht_insert_ct); 937 baij->ht_total_ct = 0; 938 baij->ht_insert_ct = 0; 939 } 940 #endif 941 if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) { 942 ierr = MatCreateHashTable_MPIBAIJ_Private(mat,baij->ht_fact); CHKERRQ(ierr); 943 mat->ops->setvalues = MatSetValues_MPIBAIJ_HT; 944 mat->ops->setvaluesblocked = MatSetValuesBlocked_MPIBAIJ_HT; 945 } 946 947 if (baij->rowvalues) {PetscFree(baij->rowvalues); baij->rowvalues = 0;} 948 PetscFunctionReturn(0); 949 } 950 951 #undef __FUNC__ 952 #define __FUNC__ "MatView_MPIBAIJ_Binary" 953 static int MatView_MPIBAIJ_Binary(Mat mat,Viewer viewer) 954 { 955 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 956 int ierr; 957 958 PetscFunctionBegin; 959 if (baij->size == 1) { 960 ierr = MatView(baij->A,viewer); CHKERRQ(ierr); 961 } else SETERRQ(PETSC_ERR_SUP,0,"Only uniprocessor output supported"); 962 PetscFunctionReturn(0); 963 } 964 965 #undef __FUNC__ 966 #define __FUNC__ "MatView_MPIBAIJ_ASCIIorDraworMatlab" 967 static int MatView_MPIBAIJ_ASCIIorDraworMatlab(Mat mat,Viewer viewer) 968 { 969 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 970 int ierr, format,rank,bs = baij->bs; 971 FILE *fd; 972 ViewerType vtype; 973 974 PetscFunctionBegin; 975 ierr = ViewerGetType(viewer,&vtype); CHKERRQ(ierr); 976 if (vtype == ASCII_FILES_VIEWER || vtype == ASCII_FILE_VIEWER) { 977 ierr = ViewerGetFormat(viewer,&format); 978 if (format == VIEWER_FORMAT_ASCII_INFO_LONG) { 979 MatInfo info; 980 MPI_Comm_rank(mat->comm,&rank); 981 ierr = ViewerASCIIGetPointer(viewer,&fd); CHKERRQ(ierr); 982 ierr = MatGetInfo(mat,MAT_LOCAL,&info); 983 PetscSequentialPhaseBegin(mat->comm,1); 984 fprintf(fd,"[%d] Local rows %d nz %d nz alloced %d bs %d mem %d\n", 985 rank,baij->m,(int)info.nz_used*bs,(int)info.nz_allocated*bs, 986 baij->bs,(int)info.memory); 987 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info); 988 fprintf(fd,"[%d] on-diagonal part: nz %d \n",rank,(int)info.nz_used*bs); 989 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info); 990 fprintf(fd,"[%d] off-diagonal part: nz %d \n",rank,(int)info.nz_used*bs); 991 fflush(fd); 992 PetscSequentialPhaseEnd(mat->comm,1); 993 ierr = VecScatterView(baij->Mvctx,viewer); CHKERRQ(ierr); 994 PetscFunctionReturn(0); 995 } else if (format == VIEWER_FORMAT_ASCII_INFO) { 996 PetscPrintf(mat->comm," block size is %d\n",bs); 997 PetscFunctionReturn(0); 998 } 999 } 1000 1001 if (vtype == DRAW_VIEWER) { 1002 Draw draw; 1003 PetscTruth isnull; 1004 ierr = ViewerDrawGetDraw(viewer,&draw); CHKERRQ(ierr); 1005 ierr = DrawIsNull(draw,&isnull); CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1006 } 1007 1008 if (vtype == ASCII_FILE_VIEWER) { 1009 ierr = ViewerASCIIGetPointer(viewer,&fd); CHKERRQ(ierr); 1010 PetscSequentialPhaseBegin(mat->comm,1); 1011 fprintf(fd,"[%d] rows %d starts %d ends %d cols %d starts %d ends %d\n", 1012 baij->rank,baij->m,baij->rstart*bs,baij->rend*bs,baij->n, 1013 baij->cstart*bs,baij->cend*bs); 1014 ierr = MatView(baij->A,viewer); CHKERRQ(ierr); 1015 ierr = MatView(baij->B,viewer); CHKERRQ(ierr); 1016 fflush(fd); 1017 PetscSequentialPhaseEnd(mat->comm,1); 1018 } else { 1019 int size = baij->size; 1020 rank = baij->rank; 1021 if (size == 1) { 1022 ierr = MatView(baij->A,viewer); CHKERRQ(ierr); 1023 } else { 1024 /* assemble the entire matrix onto first processor. */ 1025 Mat A; 1026 Mat_SeqBAIJ *Aloc; 1027 int M = baij->M, N = baij->N,*ai,*aj,col,i,j,k,*rvals; 1028 int mbs=baij->mbs; 1029 Scalar *a; 1030 1031 if (!rank) { 1032 ierr = MatCreateMPIBAIJ(mat->comm,baij->bs,M,N,M,N,0,PETSC_NULL,0,PETSC_NULL,&A);CHKERRQ(ierr); 1033 } else { 1034 ierr = MatCreateMPIBAIJ(mat->comm,baij->bs,0,0,M,N,0,PETSC_NULL,0,PETSC_NULL,&A);CHKERRQ(ierr); 1035 } 1036 PLogObjectParent(mat,A); 1037 1038 /* copy over the A part */ 1039 Aloc = (Mat_SeqBAIJ*) baij->A->data; 1040 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1041 rvals = (int *) PetscMalloc(bs*sizeof(int)); CHKPTRQ(rvals); 1042 1043 for ( i=0; i<mbs; i++ ) { 1044 rvals[0] = bs*(baij->rstart + i); 1045 for ( j=1; j<bs; j++ ) { rvals[j] = rvals[j-1] + 1; } 1046 for ( j=ai[i]; j<ai[i+1]; j++ ) { 1047 col = (baij->cstart+aj[j])*bs; 1048 for (k=0; k<bs; k++ ) { 1049 ierr = MatSetValues(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1050 col++; a += bs; 1051 } 1052 } 1053 } 1054 /* copy over the B part */ 1055 Aloc = (Mat_SeqBAIJ*) baij->B->data; 1056 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1057 for ( i=0; i<mbs; i++ ) { 1058 rvals[0] = bs*(baij->rstart + i); 1059 for ( j=1; j<bs; j++ ) { rvals[j] = rvals[j-1] + 1; } 1060 for ( j=ai[i]; j<ai[i+1]; j++ ) { 1061 col = baij->garray[aj[j]]*bs; 1062 for (k=0; k<bs; k++ ) { 1063 ierr = MatSetValues(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1064 col++; a += bs; 1065 } 1066 } 1067 } 1068 PetscFree(rvals); 1069 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1070 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1071 /* 1072 Everyone has to call to draw the matrix since the graphics waits are 1073 synchronized across all processors that share the Draw object 1074 */ 1075 if (!rank || vtype == DRAW_VIEWER) { 1076 ierr = MatView(((Mat_MPIBAIJ*)(A->data))->A,viewer); CHKERRQ(ierr); 1077 } 1078 ierr = MatDestroy(A); CHKERRQ(ierr); 1079 } 1080 } 1081 PetscFunctionReturn(0); 1082 } 1083 1084 1085 1086 #undef __FUNC__ 1087 #define __FUNC__ "MatView_MPIBAIJ" 1088 int MatView_MPIBAIJ(Mat mat,Viewer viewer) 1089 { 1090 int ierr; 1091 ViewerType vtype; 1092 1093 PetscFunctionBegin; 1094 ierr = ViewerGetType(viewer,&vtype); CHKERRQ(ierr); 1095 if (vtype == ASCII_FILE_VIEWER || vtype == ASCII_FILES_VIEWER || 1096 vtype == DRAW_VIEWER || vtype == MATLAB_VIEWER) { 1097 ierr = MatView_MPIBAIJ_ASCIIorDraworMatlab(mat,viewer); CHKERRQ(ierr); 1098 } else if (vtype == BINARY_FILE_VIEWER) { 1099 ierr = MatView_MPIBAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1100 } else { 1101 SETERRQ(1,1,"Viewer type not supported by PETSc object"); 1102 } 1103 PetscFunctionReturn(0); 1104 } 1105 1106 #undef __FUNC__ 1107 #define __FUNC__ "MatDestroy_MPIBAIJ" 1108 int MatDestroy_MPIBAIJ(Mat mat) 1109 { 1110 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 1111 int ierr; 1112 1113 PetscFunctionBegin; 1114 #if defined(USE_PETSC_LOG) 1115 PLogObjectState((PetscObject)mat,"Rows=%d, Cols=%d",baij->M,baij->N); 1116 #endif 1117 1118 ierr = StashDestroy_Private(&baij->stash); CHKERRQ(ierr); 1119 PetscFree(baij->rowners); 1120 ierr = MatDestroy(baij->A); CHKERRQ(ierr); 1121 ierr = MatDestroy(baij->B); CHKERRQ(ierr); 1122 if (baij->colmap) PetscFree(baij->colmap); 1123 if (baij->garray) PetscFree(baij->garray); 1124 if (baij->lvec) VecDestroy(baij->lvec); 1125 if (baij->Mvctx) VecScatterDestroy(baij->Mvctx); 1126 if (baij->rowvalues) PetscFree(baij->rowvalues); 1127 if (baij->barray) PetscFree(baij->barray); 1128 if (baij->hd) PetscFree(baij->hd); 1129 PetscFree(baij); 1130 PLogObjectDestroy(mat); 1131 PetscHeaderDestroy(mat); 1132 PetscFunctionReturn(0); 1133 } 1134 1135 #undef __FUNC__ 1136 #define __FUNC__ "MatMult_MPIBAIJ" 1137 int MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy) 1138 { 1139 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data; 1140 int ierr, nt; 1141 1142 PetscFunctionBegin; 1143 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1144 if (nt != a->n) { 1145 SETERRQ(PETSC_ERR_ARG_SIZ,0,"Incompatible partition of A and xx"); 1146 } 1147 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 1148 if (nt != a->m) { 1149 SETERRQ(PETSC_ERR_ARG_SIZ,0,"Incompatible parition of A and yy"); 1150 } 1151 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1152 ierr = (*a->A->ops->mult)(a->A,xx,yy); CHKERRQ(ierr); 1153 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1154 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy); CHKERRQ(ierr); 1155 ierr = VecScatterPostRecvs(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1156 PetscFunctionReturn(0); 1157 } 1158 1159 #undef __FUNC__ 1160 #define __FUNC__ "MatMultAdd_MPIBAIJ" 1161 int MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1162 { 1163 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data; 1164 int ierr; 1165 1166 PetscFunctionBegin; 1167 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1168 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz); CHKERRQ(ierr); 1169 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1170 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz); CHKERRQ(ierr); 1171 PetscFunctionReturn(0); 1172 } 1173 1174 #undef __FUNC__ 1175 #define __FUNC__ "MatMultTrans_MPIBAIJ" 1176 int MatMultTrans_MPIBAIJ(Mat A,Vec xx,Vec yy) 1177 { 1178 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data; 1179 int ierr; 1180 1181 PetscFunctionBegin; 1182 /* do nondiagonal part */ 1183 ierr = (*a->B->ops->multtrans)(a->B,xx,a->lvec); CHKERRQ(ierr); 1184 /* send it on its way */ 1185 ierr = VecScatterBegin(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1186 /* do local part */ 1187 ierr = (*a->A->ops->multtrans)(a->A,xx,yy); CHKERRQ(ierr); 1188 /* receive remote parts: note this assumes the values are not actually */ 1189 /* inserted in yy until the next line, which is true for my implementation*/ 1190 /* but is not perhaps always true. */ 1191 ierr = VecScatterEnd(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1192 PetscFunctionReturn(0); 1193 } 1194 1195 #undef __FUNC__ 1196 #define __FUNC__ "MatMultTransAdd_MPIBAIJ" 1197 int MatMultTransAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1198 { 1199 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data; 1200 int ierr; 1201 1202 PetscFunctionBegin; 1203 /* do nondiagonal part */ 1204 ierr = (*a->B->ops->multtrans)(a->B,xx,a->lvec); CHKERRQ(ierr); 1205 /* send it on its way */ 1206 ierr = VecScatterBegin(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx); CHKERRQ(ierr); 1207 /* do local part */ 1208 ierr = (*a->A->ops->multtransadd)(a->A,xx,yy,zz); CHKERRQ(ierr); 1209 /* receive remote parts: note this assumes the values are not actually */ 1210 /* inserted in yy until the next line, which is true for my implementation*/ 1211 /* but is not perhaps always true. */ 1212 ierr = VecScatterEnd(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx); CHKERRQ(ierr); 1213 PetscFunctionReturn(0); 1214 } 1215 1216 /* 1217 This only works correctly for square matrices where the subblock A->A is the 1218 diagonal block 1219 */ 1220 #undef __FUNC__ 1221 #define __FUNC__ "MatGetDiagonal_MPIBAIJ" 1222 int MatGetDiagonal_MPIBAIJ(Mat A,Vec v) 1223 { 1224 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data; 1225 int ierr; 1226 1227 PetscFunctionBegin; 1228 if (a->M != a->N) SETERRQ(PETSC_ERR_SUP,0,"Supports only square matrix where A->A is diag block"); 1229 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1230 PetscFunctionReturn(0); 1231 } 1232 1233 #undef __FUNC__ 1234 #define __FUNC__ "MatScale_MPIBAIJ" 1235 int MatScale_MPIBAIJ(Scalar *aa,Mat A) 1236 { 1237 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data; 1238 int ierr; 1239 1240 PetscFunctionBegin; 1241 ierr = MatScale(aa,a->A); CHKERRQ(ierr); 1242 ierr = MatScale(aa,a->B); CHKERRQ(ierr); 1243 PetscFunctionReturn(0); 1244 } 1245 1246 #undef __FUNC__ 1247 #define __FUNC__ "MatGetSize_MPIBAIJ" 1248 int MatGetSize_MPIBAIJ(Mat matin,int *m,int *n) 1249 { 1250 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ *) matin->data; 1251 1252 PetscFunctionBegin; 1253 if (m) *m = mat->M; 1254 if (n) *n = mat->N; 1255 PetscFunctionReturn(0); 1256 } 1257 1258 #undef __FUNC__ 1259 #define __FUNC__ "MatGetLocalSize_MPIBAIJ" 1260 int MatGetLocalSize_MPIBAIJ(Mat matin,int *m,int *n) 1261 { 1262 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ *) matin->data; 1263 1264 PetscFunctionBegin; 1265 *m = mat->m; *n = mat->n; 1266 PetscFunctionReturn(0); 1267 } 1268 1269 #undef __FUNC__ 1270 #define __FUNC__ "MatGetOwnershipRange_MPIBAIJ" 1271 int MatGetOwnershipRange_MPIBAIJ(Mat matin,int *m,int *n) 1272 { 1273 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ *) matin->data; 1274 1275 PetscFunctionBegin; 1276 *m = mat->rstart*mat->bs; *n = mat->rend*mat->bs; 1277 PetscFunctionReturn(0); 1278 } 1279 1280 extern int MatGetRow_SeqBAIJ(Mat,int,int*,int**,Scalar**); 1281 extern int MatRestoreRow_SeqBAIJ(Mat,int,int*,int**,Scalar**); 1282 1283 #undef __FUNC__ 1284 #define __FUNC__ "MatGetRow_MPIBAIJ" 1285 int MatGetRow_MPIBAIJ(Mat matin,int row,int *nz,int **idx,Scalar **v) 1286 { 1287 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ *) matin->data; 1288 Scalar *vworkA, *vworkB, **pvA, **pvB,*v_p; 1289 int bs = mat->bs, bs2 = mat->bs2, i, ierr, *cworkA, *cworkB, **pcA, **pcB; 1290 int nztot, nzA, nzB, lrow, brstart = mat->rstart*bs, brend = mat->rend*bs; 1291 int *cmap, *idx_p,cstart = mat->cstart; 1292 1293 PetscFunctionBegin; 1294 if (mat->getrowactive == PETSC_TRUE) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Already active"); 1295 mat->getrowactive = PETSC_TRUE; 1296 1297 if (!mat->rowvalues && (idx || v)) { 1298 /* 1299 allocate enough space to hold information from the longest row. 1300 */ 1301 Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ *) mat->A->data,*Ba = (Mat_SeqBAIJ *) mat->B->data; 1302 int max = 1,mbs = mat->mbs,tmp; 1303 for ( i=0; i<mbs; i++ ) { 1304 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1305 if (max < tmp) { max = tmp; } 1306 } 1307 mat->rowvalues = (Scalar *) PetscMalloc( max*bs2*(sizeof(int)+sizeof(Scalar))); 1308 CHKPTRQ(mat->rowvalues); 1309 mat->rowindices = (int *) (mat->rowvalues + max*bs2); 1310 } 1311 1312 if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,0,"Only local rows") 1313 lrow = row - brstart; 1314 1315 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1316 if (!v) {pvA = 0; pvB = 0;} 1317 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1318 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA); CHKERRQ(ierr); 1319 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB); CHKERRQ(ierr); 1320 nztot = nzA + nzB; 1321 1322 cmap = mat->garray; 1323 if (v || idx) { 1324 if (nztot) { 1325 /* Sort by increasing column numbers, assuming A and B already sorted */ 1326 int imark = -1; 1327 if (v) { 1328 *v = v_p = mat->rowvalues; 1329 for ( i=0; i<nzB; i++ ) { 1330 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1331 else break; 1332 } 1333 imark = i; 1334 for ( i=0; i<nzA; i++ ) v_p[imark+i] = vworkA[i]; 1335 for ( i=imark; i<nzB; i++ ) v_p[nzA+i] = vworkB[i]; 1336 } 1337 if (idx) { 1338 *idx = idx_p = mat->rowindices; 1339 if (imark > -1) { 1340 for ( i=0; i<imark; i++ ) { 1341 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1342 } 1343 } else { 1344 for ( i=0; i<nzB; i++ ) { 1345 if (cmap[cworkB[i]/bs] < cstart) 1346 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1347 else break; 1348 } 1349 imark = i; 1350 } 1351 for ( i=0; i<nzA; i++ ) idx_p[imark+i] = cstart*bs + cworkA[i]; 1352 for ( i=imark; i<nzB; i++ ) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1353 } 1354 } else { 1355 if (idx) *idx = 0; 1356 if (v) *v = 0; 1357 } 1358 } 1359 *nz = nztot; 1360 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA); CHKERRQ(ierr); 1361 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB); CHKERRQ(ierr); 1362 PetscFunctionReturn(0); 1363 } 1364 1365 #undef __FUNC__ 1366 #define __FUNC__ "MatRestoreRow_MPIBAIJ" 1367 int MatRestoreRow_MPIBAIJ(Mat mat,int row,int *nz,int **idx,Scalar **v) 1368 { 1369 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 1370 1371 PetscFunctionBegin; 1372 if (baij->getrowactive == PETSC_FALSE) { 1373 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"MatGetRow not called"); 1374 } 1375 baij->getrowactive = PETSC_FALSE; 1376 PetscFunctionReturn(0); 1377 } 1378 1379 #undef __FUNC__ 1380 #define __FUNC__ "MatGetBlockSize_MPIBAIJ" 1381 int MatGetBlockSize_MPIBAIJ(Mat mat,int *bs) 1382 { 1383 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 1384 1385 PetscFunctionBegin; 1386 *bs = baij->bs; 1387 PetscFunctionReturn(0); 1388 } 1389 1390 #undef __FUNC__ 1391 #define __FUNC__ "MatZeroEntries_MPIBAIJ" 1392 int MatZeroEntries_MPIBAIJ(Mat A) 1393 { 1394 Mat_MPIBAIJ *l = (Mat_MPIBAIJ *) A->data; 1395 int ierr; 1396 1397 PetscFunctionBegin; 1398 ierr = MatZeroEntries(l->A); CHKERRQ(ierr); 1399 ierr = MatZeroEntries(l->B); CHKERRQ(ierr); 1400 PetscFunctionReturn(0); 1401 } 1402 1403 #undef __FUNC__ 1404 #define __FUNC__ "MatGetInfo_MPIBAIJ" 1405 int MatGetInfo_MPIBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1406 { 1407 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) matin->data; 1408 Mat A = a->A, B = a->B; 1409 int ierr; 1410 double isend[5], irecv[5]; 1411 1412 PetscFunctionBegin; 1413 info->block_size = (double)a->bs; 1414 ierr = MatGetInfo(A,MAT_LOCAL,info); CHKERRQ(ierr); 1415 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->memory; 1416 ierr = MatGetInfo(B,MAT_LOCAL,info); CHKERRQ(ierr); 1417 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->memory; 1418 if (flag == MAT_LOCAL) { 1419 info->nz_used = isend[0]; 1420 info->nz_allocated = isend[1]; 1421 info->nz_unneeded = isend[2]; 1422 info->memory = isend[3]; 1423 info->mallocs = isend[4]; 1424 } else if (flag == MAT_GLOBAL_MAX) { 1425 ierr = MPI_Allreduce(isend,irecv,5,MPI_INT,MPI_MAX,matin->comm);CHKERRQ(ierr); 1426 info->nz_used = irecv[0]; 1427 info->nz_allocated = irecv[1]; 1428 info->nz_unneeded = irecv[2]; 1429 info->memory = irecv[3]; 1430 info->mallocs = irecv[4]; 1431 } else if (flag == MAT_GLOBAL_SUM) { 1432 ierr = MPI_Allreduce(isend,irecv,5,MPI_INT,MPI_SUM,matin->comm);CHKERRQ(ierr); 1433 info->nz_used = irecv[0]; 1434 info->nz_allocated = irecv[1]; 1435 info->nz_unneeded = irecv[2]; 1436 info->memory = irecv[3]; 1437 info->mallocs = irecv[4]; 1438 } 1439 info->rows_global = (double)a->M; 1440 info->columns_global = (double)a->N; 1441 info->rows_local = (double)a->m; 1442 info->columns_local = (double)a->N; 1443 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1444 info->fill_ratio_needed = 0; 1445 info->factor_mallocs = 0; 1446 PetscFunctionReturn(0); 1447 } 1448 1449 #undef __FUNC__ 1450 #define __FUNC__ "MatSetOption_MPIBAIJ" 1451 int MatSetOption_MPIBAIJ(Mat A,MatOption op) 1452 { 1453 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data; 1454 1455 PetscFunctionBegin; 1456 if (op == MAT_NO_NEW_NONZERO_LOCATIONS || 1457 op == MAT_YES_NEW_NONZERO_LOCATIONS || 1458 op == MAT_COLUMNS_UNSORTED || 1459 op == MAT_COLUMNS_SORTED || 1460 op == MAT_NEW_NONZERO_ALLOCATION_ERROR || 1461 op == MAT_NEW_NONZERO_LOCATION_ERROR) { 1462 MatSetOption(a->A,op); 1463 MatSetOption(a->B,op); 1464 } else if (op == MAT_ROW_ORIENTED) { 1465 a->roworiented = 1; 1466 MatSetOption(a->A,op); 1467 MatSetOption(a->B,op); 1468 } else if (op == MAT_ROWS_SORTED || 1469 op == MAT_ROWS_UNSORTED || 1470 op == MAT_SYMMETRIC || 1471 op == MAT_STRUCTURALLY_SYMMETRIC || 1472 op == MAT_YES_NEW_DIAGONALS || 1473 op == MAT_USE_HASH_TABLE) 1474 PLogInfo(A,"Info:MatSetOption_MPIBAIJ:Option ignored\n"); 1475 else if (op == MAT_COLUMN_ORIENTED) { 1476 a->roworiented = 0; 1477 MatSetOption(a->A,op); 1478 MatSetOption(a->B,op); 1479 } else if (op == MAT_IGNORE_OFF_PROC_ENTRIES) { 1480 a->donotstash = 1; 1481 } else if (op == MAT_NO_NEW_DIAGONALS) { 1482 SETERRQ(PETSC_ERR_SUP,0,"MAT_NO_NEW_DIAGONALS"); 1483 } else if (op == MAT_USE_HASH_TABLE) { 1484 a->ht_flag = 1; 1485 } else { 1486 SETERRQ(PETSC_ERR_SUP,0,"unknown option"); 1487 } 1488 PetscFunctionReturn(0); 1489 } 1490 1491 #undef __FUNC__ 1492 #define __FUNC__ "MatTranspose_MPIBAIJ(" 1493 int MatTranspose_MPIBAIJ(Mat A,Mat *matout) 1494 { 1495 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) A->data; 1496 Mat_SeqBAIJ *Aloc; 1497 Mat B; 1498 int ierr,M=baij->M,N=baij->N,*ai,*aj,i,*rvals,j,k,col; 1499 int bs=baij->bs,mbs=baij->mbs; 1500 Scalar *a; 1501 1502 PetscFunctionBegin; 1503 if (matout == PETSC_NULL && M != N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Square matrix only for in-place"); 1504 ierr = MatCreateMPIBAIJ(A->comm,baij->bs,PETSC_DECIDE,PETSC_DECIDE,N,M,0,PETSC_NULL,0,PETSC_NULL,&B); 1505 CHKERRQ(ierr); 1506 1507 /* copy over the A part */ 1508 Aloc = (Mat_SeqBAIJ*) baij->A->data; 1509 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1510 rvals = (int *) PetscMalloc(bs*sizeof(int)); CHKPTRQ(rvals); 1511 1512 for ( i=0; i<mbs; i++ ) { 1513 rvals[0] = bs*(baij->rstart + i); 1514 for ( j=1; j<bs; j++ ) { rvals[j] = rvals[j-1] + 1; } 1515 for ( j=ai[i]; j<ai[i+1]; j++ ) { 1516 col = (baij->cstart+aj[j])*bs; 1517 for (k=0; k<bs; k++ ) { 1518 ierr = MatSetValues(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1519 col++; a += bs; 1520 } 1521 } 1522 } 1523 /* copy over the B part */ 1524 Aloc = (Mat_SeqBAIJ*) baij->B->data; 1525 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1526 for ( i=0; i<mbs; i++ ) { 1527 rvals[0] = bs*(baij->rstart + i); 1528 for ( j=1; j<bs; j++ ) { rvals[j] = rvals[j-1] + 1; } 1529 for ( j=ai[i]; j<ai[i+1]; j++ ) { 1530 col = baij->garray[aj[j]]*bs; 1531 for (k=0; k<bs; k++ ) { 1532 ierr = MatSetValues(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1533 col++; a += bs; 1534 } 1535 } 1536 } 1537 PetscFree(rvals); 1538 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1539 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1540 1541 if (matout != PETSC_NULL) { 1542 *matout = B; 1543 } else { 1544 PetscOps *Abops; 1545 struct _MatOps *Aops; 1546 1547 /* This isn't really an in-place transpose .... but free data structures from baij */ 1548 PetscFree(baij->rowners); 1549 ierr = MatDestroy(baij->A); CHKERRQ(ierr); 1550 ierr = MatDestroy(baij->B); CHKERRQ(ierr); 1551 if (baij->colmap) PetscFree(baij->colmap); 1552 if (baij->garray) PetscFree(baij->garray); 1553 if (baij->lvec) VecDestroy(baij->lvec); 1554 if (baij->Mvctx) VecScatterDestroy(baij->Mvctx); 1555 PetscFree(baij); 1556 1557 /* 1558 This is horrible, horrible code. We need to keep the 1559 A pointers for the bops and ops but copy everything 1560 else from C. 1561 */ 1562 Abops = A->bops; 1563 Aops = A->ops; 1564 PetscMemcpy(A,B,sizeof(struct _p_Mat)); 1565 A->bops = Abops; 1566 A->ops = Aops; 1567 1568 PetscHeaderDestroy(B); 1569 } 1570 PetscFunctionReturn(0); 1571 } 1572 1573 #undef __FUNC__ 1574 #define __FUNC__ "MatDiagonalScale_MPIBAIJ" 1575 int MatDiagonalScale_MPIBAIJ(Mat A,Vec ll,Vec rr) 1576 { 1577 Mat a = ((Mat_MPIBAIJ *) A->data)->A; 1578 Mat b = ((Mat_MPIBAIJ *) A->data)->B; 1579 int ierr,s1,s2,s3; 1580 1581 PetscFunctionBegin; 1582 if (ll) { 1583 ierr = VecGetLocalSize(ll,&s1); CHKERRQ(ierr); 1584 ierr = MatGetLocalSize(A,&s2,&s3); CHKERRQ(ierr); 1585 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,0,"non-conforming local sizes"); 1586 ierr = MatDiagonalScale(a,ll,0); CHKERRQ(ierr); 1587 ierr = MatDiagonalScale(b,ll,0); CHKERRQ(ierr); 1588 } 1589 if (rr) SETERRQ(PETSC_ERR_SUP,0,"not supported for right vector"); 1590 PetscFunctionReturn(0); 1591 } 1592 1593 #undef __FUNC__ 1594 #define __FUNC__ "MatZeroRows_MPIBAIJ" 1595 int MatZeroRows_MPIBAIJ(Mat A,IS is,Scalar *diag) 1596 { 1597 Mat_MPIBAIJ *l = (Mat_MPIBAIJ *) A->data; 1598 int i,ierr,N, *rows,*owners = l->rowners,size = l->size; 1599 int *procs,*nprocs,j,found,idx,nsends,*work,row; 1600 int nmax,*svalues,*starts,*owner,nrecvs,rank = l->rank; 1601 int *rvalues,tag = A->tag,count,base,slen,n,*source; 1602 int *lens,imdex,*lrows,*values,bs=l->bs,rstart_bs=l->rstart_bs; 1603 MPI_Comm comm = A->comm; 1604 MPI_Request *send_waits,*recv_waits; 1605 MPI_Status recv_status,*send_status; 1606 IS istmp; 1607 1608 PetscFunctionBegin; 1609 ierr = ISGetSize(is,&N); CHKERRQ(ierr); 1610 ierr = ISGetIndices(is,&rows); CHKERRQ(ierr); 1611 1612 /* first count number of contributors to each processor */ 1613 nprocs = (int *) PetscMalloc( 2*size*sizeof(int) ); CHKPTRQ(nprocs); 1614 PetscMemzero(nprocs,2*size*sizeof(int)); procs = nprocs + size; 1615 owner = (int *) PetscMalloc((N+1)*sizeof(int)); CHKPTRQ(owner); /* see note*/ 1616 for ( i=0; i<N; i++ ) { 1617 idx = rows[i]; 1618 found = 0; 1619 for ( j=0; j<size; j++ ) { 1620 if (idx >= owners[j]*bs && idx < owners[j+1]*bs) { 1621 nprocs[j]++; procs[j] = 1; owner[i] = j; found = 1; break; 1622 } 1623 } 1624 if (!found) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Index out of range"); 1625 } 1626 nsends = 0; for ( i=0; i<size; i++ ) { nsends += procs[i];} 1627 1628 /* inform other processors of number of messages and max length*/ 1629 work = (int *) PetscMalloc( size*sizeof(int) ); CHKPTRQ(work); 1630 ierr = MPI_Allreduce( procs, work,size,MPI_INT,MPI_SUM,comm);CHKERRQ(ierr); 1631 nrecvs = work[rank]; 1632 ierr = MPI_Allreduce( nprocs, work,size,MPI_INT,MPI_MAX,comm);CHKERRQ(ierr); 1633 nmax = work[rank]; 1634 PetscFree(work); 1635 1636 /* post receives: */ 1637 rvalues = (int *) PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(int)); CHKPTRQ(rvalues); 1638 recv_waits = (MPI_Request *) PetscMalloc((nrecvs+1)*sizeof(MPI_Request));CHKPTRQ(recv_waits); 1639 for ( i=0; i<nrecvs; i++ ) { 1640 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPI_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 1641 } 1642 1643 /* do sends: 1644 1) starts[i] gives the starting index in svalues for stuff going to 1645 the ith processor 1646 */ 1647 svalues = (int *) PetscMalloc( (N+1)*sizeof(int) ); CHKPTRQ(svalues); 1648 send_waits = (MPI_Request *) PetscMalloc( (nsends+1)*sizeof(MPI_Request));CHKPTRQ(send_waits); 1649 starts = (int *) PetscMalloc( (size+1)*sizeof(int) ); CHKPTRQ(starts); 1650 starts[0] = 0; 1651 for ( i=1; i<size; i++ ) { starts[i] = starts[i-1] + nprocs[i-1];} 1652 for ( i=0; i<N; i++ ) { 1653 svalues[starts[owner[i]]++] = rows[i]; 1654 } 1655 ISRestoreIndices(is,&rows); 1656 1657 starts[0] = 0; 1658 for ( i=1; i<size+1; i++ ) { starts[i] = starts[i-1] + nprocs[i-1];} 1659 count = 0; 1660 for ( i=0; i<size; i++ ) { 1661 if (procs[i]) { 1662 ierr = MPI_Isend(svalues+starts[i],nprocs[i],MPI_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 1663 } 1664 } 1665 PetscFree(starts); 1666 1667 base = owners[rank]*bs; 1668 1669 /* wait on receives */ 1670 lens = (int *) PetscMalloc( 2*(nrecvs+1)*sizeof(int) ); CHKPTRQ(lens); 1671 source = lens + nrecvs; 1672 count = nrecvs; slen = 0; 1673 while (count) { 1674 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 1675 /* unpack receives into our local space */ 1676 ierr = MPI_Get_count(&recv_status,MPI_INT,&n);CHKERRQ(ierr); 1677 source[imdex] = recv_status.MPI_SOURCE; 1678 lens[imdex] = n; 1679 slen += n; 1680 count--; 1681 } 1682 PetscFree(recv_waits); 1683 1684 /* move the data into the send scatter */ 1685 lrows = (int *) PetscMalloc( (slen+1)*sizeof(int) ); CHKPTRQ(lrows); 1686 count = 0; 1687 for ( i=0; i<nrecvs; i++ ) { 1688 values = rvalues + i*nmax; 1689 for ( j=0; j<lens[i]; j++ ) { 1690 lrows[count++] = values[j] - base; 1691 } 1692 } 1693 PetscFree(rvalues); PetscFree(lens); 1694 PetscFree(owner); PetscFree(nprocs); 1695 1696 /* actually zap the local rows */ 1697 ierr = ISCreateGeneral(PETSC_COMM_SELF,slen,lrows,&istmp);CHKERRQ(ierr); 1698 PLogObjectParent(A,istmp); 1699 1700 ierr = MatZeroRows(l->A,istmp,0); CHKERRQ(ierr); 1701 ierr = MatZeroRows(l->B,istmp,0); CHKERRQ(ierr); 1702 ierr = ISDestroy(istmp); CHKERRQ(ierr); 1703 1704 if (diag) { 1705 for ( i = 0; i < slen; i++ ) { 1706 row = lrows[i] + rstart_bs; 1707 ierr = MatSetValues(A,1,&row,1,&row,diag,INSERT_VALUES); CHKERRQ(ierr); 1708 } 1709 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1710 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1711 } 1712 PetscFree(lrows); 1713 1714 /* wait on sends */ 1715 if (nsends) { 1716 send_status = (MPI_Status *) PetscMalloc(nsends*sizeof(MPI_Status));CHKPTRQ(send_status); 1717 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 1718 PetscFree(send_status); 1719 } 1720 PetscFree(send_waits); PetscFree(svalues); 1721 1722 PetscFunctionReturn(0); 1723 } 1724 extern int MatPrintHelp_SeqBAIJ(Mat); 1725 #undef __FUNC__ 1726 #define __FUNC__ "MatPrintHelp_MPIBAIJ" 1727 int MatPrintHelp_MPIBAIJ(Mat A) 1728 { 1729 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*) A->data; 1730 MPI_Comm comm = A->comm; 1731 static int called = 0; 1732 int ierr; 1733 1734 PetscFunctionBegin; 1735 if (!a->rank) { 1736 ierr = MatPrintHelp_SeqBAIJ(a->A);CHKERRQ(ierr); 1737 } 1738 if (called) {PetscFunctionReturn(0);} else called = 1; 1739 (*PetscHelpPrintf)(comm," Options for MATMPIBAIJ matrix format (the defaults):\n"); 1740 (*PetscHelpPrintf)(comm," -mat_use_hash_table <factor>: Use hashtable for efficient matrix assembly\n"); 1741 PetscFunctionReturn(0); 1742 } 1743 1744 #undef __FUNC__ 1745 #define __FUNC__ "MatSetUnfactored_MPIBAIJ" 1746 int MatSetUnfactored_MPIBAIJ(Mat A) 1747 { 1748 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*) A->data; 1749 int ierr; 1750 1751 PetscFunctionBegin; 1752 ierr = MatSetUnfactored(a->A); CHKERRQ(ierr); 1753 PetscFunctionReturn(0); 1754 } 1755 1756 static int MatConvertSameType_MPIBAIJ(Mat,Mat *,int); 1757 1758 /* -------------------------------------------------------------------*/ 1759 static struct _MatOps MatOps = { 1760 MatSetValues_MPIBAIJ,MatGetRow_MPIBAIJ,MatRestoreRow_MPIBAIJ,MatMult_MPIBAIJ, 1761 MatMultAdd_MPIBAIJ,MatMultTrans_MPIBAIJ,MatMultTransAdd_MPIBAIJ,0, 1762 0,0,0,0, 1763 0,0,MatTranspose_MPIBAIJ,MatGetInfo_MPIBAIJ, 1764 0,MatGetDiagonal_MPIBAIJ,MatDiagonalScale_MPIBAIJ,MatNorm_MPIBAIJ, 1765 MatAssemblyBegin_MPIBAIJ,MatAssemblyEnd_MPIBAIJ,0,MatSetOption_MPIBAIJ, 1766 MatZeroEntries_MPIBAIJ,MatZeroRows_MPIBAIJ,0, 1767 0,0,0,MatGetSize_MPIBAIJ, 1768 MatGetLocalSize_MPIBAIJ,MatGetOwnershipRange_MPIBAIJ,0,0, 1769 0,0,MatConvertSameType_MPIBAIJ,0,0, 1770 0,0,0,MatGetSubMatrices_MPIBAIJ, 1771 MatIncreaseOverlap_MPIBAIJ,MatGetValues_MPIBAIJ,0,MatPrintHelp_MPIBAIJ, 1772 MatScale_MPIBAIJ,0,0,0,MatGetBlockSize_MPIBAIJ, 1773 0,0,0,0,0,0,MatSetUnfactored_MPIBAIJ,0,MatSetValuesBlocked_MPIBAIJ}; 1774 1775 1776 #undef __FUNC__ 1777 #define __FUNC__ "MatCreateMPIBAIJ" 1778 /*@C 1779 MatCreateMPIBAIJ - Creates a sparse parallel matrix in block AIJ format 1780 (block compressed row). For good matrix assembly performance 1781 the user should preallocate the matrix storage by setting the parameters 1782 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1783 performance can be increased by more than a factor of 50. 1784 1785 Collective on MPI_Comm 1786 1787 Input Parameters: 1788 + comm - MPI communicator 1789 . bs - size of blockk 1790 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1791 This value should be the same as the local size used in creating the 1792 y vector for the matrix-vector product y = Ax. 1793 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1794 This value should be the same as the local size used in creating the 1795 x vector for the matrix-vector product y = Ax. 1796 . M - number of global rows (or PETSC_DECIDE to have calculated if m is given) 1797 . N - number of global columns (or PETSC_DECIDE to have calculated if n is given) 1798 . d_nz - number of block nonzeros per block row in diagonal portion of local 1799 submatrix (same for all local rows) 1800 . d_nzz - array containing the number of block nonzeros in the various block rows 1801 of the in diagonal portion of the local (possibly different for each block 1802 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 1803 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1804 submatrix (same for all local rows). 1805 - o_nzz - array containing the number of nonzeros in the various block rows of the 1806 off-diagonal portion of the local submatrix (possibly different for 1807 each block row) or PETSC_NULL. 1808 1809 Output Parameter: 1810 . A - the matrix 1811 1812 Options Database Keys: 1813 . -mat_no_unroll - uses code that does not unroll the loops in the 1814 block calculations (much slower) 1815 . -mat_block_size - size of the blocks to use 1816 1817 Notes: 1818 The user MUST specify either the local or global matrix dimensions 1819 (possibly both). 1820 1821 Storage Information: 1822 For a square global matrix we define each processor's diagonal portion 1823 to be its local rows and the corresponding columns (a square submatrix); 1824 each processor's off-diagonal portion encompasses the remainder of the 1825 local matrix (a rectangular submatrix). 1826 1827 The user can specify preallocated storage for the diagonal part of 1828 the local submatrix with either d_nz or d_nnz (not both). Set 1829 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1830 memory allocation. Likewise, specify preallocated storage for the 1831 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1832 1833 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1834 the figure below we depict these three local rows and all columns (0-11). 1835 1836 .vb 1837 0 1 2 3 4 5 6 7 8 9 10 11 1838 ------------------- 1839 row 3 | o o o d d d o o o o o o 1840 row 4 | o o o d d d o o o o o o 1841 row 5 | o o o d d d o o o o o o 1842 ------------------- 1843 .ve 1844 1845 Thus, any entries in the d locations are stored in the d (diagonal) 1846 submatrix, and any entries in the o locations are stored in the 1847 o (off-diagonal) submatrix. Note that the d and the o submatrices are 1848 stored simply in the MATSEQBAIJ format for compressed row storage. 1849 1850 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 1851 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1852 In general, for PDE problems in which most nonzeros are near the diagonal, 1853 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1854 or you will get TERRIBLE performance; see the users' manual chapter on 1855 matrices. 1856 1857 .keywords: matrix, block, aij, compressed row, sparse, parallel 1858 1859 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateMPIAIJ() 1860 @*/ 1861 int MatCreateMPIBAIJ(MPI_Comm comm,int bs,int m,int n,int M,int N, 1862 int d_nz,int *d_nnz,int o_nz,int *o_nnz,Mat *A) 1863 { 1864 Mat B; 1865 Mat_MPIBAIJ *b; 1866 int ierr, i,sum[2],work[2],mbs,nbs,Mbs=PETSC_DECIDE,Nbs=PETSC_DECIDE,size,flg; 1867 1868 PetscFunctionBegin; 1869 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Invalid block size specified, must be positive"); 1870 1871 MPI_Comm_size(comm,&size); 1872 if (size == 1) { 1873 if (M == PETSC_DECIDE) M = m; 1874 if (N == PETSC_DECIDE) N = n; 1875 ierr = MatCreateSeqBAIJ(comm,bs,M,N,d_nz,d_nnz,A); CHKERRQ(ierr); 1876 PetscFunctionReturn(0); 1877 } 1878 1879 *A = 0; 1880 PetscHeaderCreate(B,_p_Mat,struct _MatOps,MAT_COOKIE,MATMPIBAIJ,comm,MatDestroy,MatView); 1881 PLogObjectCreate(B); 1882 B->data = (void *) (b = PetscNew(Mat_MPIBAIJ)); CHKPTRQ(b); 1883 PetscMemzero(b,sizeof(Mat_MPIBAIJ)); 1884 PetscMemcpy(B->ops,&MatOps,sizeof(struct _MatOps)); 1885 1886 B->ops->destroy = MatDestroy_MPIBAIJ; 1887 B->ops->view = MatView_MPIBAIJ; 1888 B->mapping = 0; 1889 B->factor = 0; 1890 B->assembled = PETSC_FALSE; 1891 1892 B->insertmode = NOT_SET_VALUES; 1893 MPI_Comm_rank(comm,&b->rank); 1894 MPI_Comm_size(comm,&b->size); 1895 1896 if ( m == PETSC_DECIDE && (d_nnz != PETSC_NULL || o_nnz != PETSC_NULL)) { 1897 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Cannot have PETSC_DECIDE rows but set d_nnz or o_nnz"); 1898 } 1899 if ( M == PETSC_DECIDE && m == PETSC_DECIDE) { 1900 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"either M or m should be specified"); 1901 } 1902 if ( N == PETSC_DECIDE && n == PETSC_DECIDE) { 1903 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"either N or n should be specified"); 1904 } 1905 if ( M != PETSC_DECIDE && m != PETSC_DECIDE) M = PETSC_DECIDE; 1906 if ( N != PETSC_DECIDE && n != PETSC_DECIDE) N = PETSC_DECIDE; 1907 1908 if (M == PETSC_DECIDE || N == PETSC_DECIDE) { 1909 work[0] = m; work[1] = n; 1910 mbs = m/bs; nbs = n/bs; 1911 ierr = MPI_Allreduce( work, sum,2,MPI_INT,MPI_SUM,comm );CHKERRQ(ierr); 1912 if (M == PETSC_DECIDE) {M = sum[0]; Mbs = M/bs;} 1913 if (N == PETSC_DECIDE) {N = sum[1]; Nbs = N/bs;} 1914 } 1915 if (m == PETSC_DECIDE) { 1916 Mbs = M/bs; 1917 if (Mbs*bs != M) SETERRQ(PETSC_ERR_ARG_SIZ,0,"No of global rows must be divisible by blocksize"); 1918 mbs = Mbs/b->size + ((Mbs % b->size) > b->rank); 1919 m = mbs*bs; 1920 } 1921 if (n == PETSC_DECIDE) { 1922 Nbs = N/bs; 1923 if (Nbs*bs != N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"No of global cols must be divisible by blocksize"); 1924 nbs = Nbs/b->size + ((Nbs % b->size) > b->rank); 1925 n = nbs*bs; 1926 } 1927 if (mbs*bs != m || nbs*bs != n) { 1928 SETERRQ(PETSC_ERR_ARG_SIZ,0,"No of local rows, cols must be divisible by blocksize"); 1929 } 1930 1931 b->m = m; B->m = m; 1932 b->n = n; B->n = n; 1933 b->N = N; B->N = N; 1934 b->M = M; B->M = M; 1935 b->bs = bs; 1936 b->bs2 = bs*bs; 1937 b->mbs = mbs; 1938 b->nbs = nbs; 1939 b->Mbs = Mbs; 1940 b->Nbs = Nbs; 1941 1942 /* build local table of row and column ownerships */ 1943 b->rowners = (int *) PetscMalloc(2*(b->size+2)*sizeof(int)); CHKPTRQ(b->rowners); 1944 PLogObjectMemory(B,2*(b->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPIBAIJ)); 1945 b->cowners = b->rowners + b->size + 2; 1946 ierr = MPI_Allgather(&mbs,1,MPI_INT,b->rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 1947 b->rowners[0] = 0; 1948 for ( i=2; i<=b->size; i++ ) { 1949 b->rowners[i] += b->rowners[i-1]; 1950 } 1951 b->rstart = b->rowners[b->rank]; 1952 b->rend = b->rowners[b->rank+1]; 1953 b->rstart_bs = b->rstart * bs; 1954 b->rend_bs = b->rend * bs; 1955 1956 ierr = MPI_Allgather(&nbs,1,MPI_INT,b->cowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 1957 b->cowners[0] = 0; 1958 for ( i=2; i<=b->size; i++ ) { 1959 b->cowners[i] += b->cowners[i-1]; 1960 } 1961 b->cstart = b->cowners[b->rank]; 1962 b->cend = b->cowners[b->rank+1]; 1963 b->cstart_bs = b->cstart * bs; 1964 b->cend_bs = b->cend * bs; 1965 1966 1967 if (d_nz == PETSC_DEFAULT) d_nz = 5; 1968 ierr = MatCreateSeqBAIJ(PETSC_COMM_SELF,bs,m,n,d_nz,d_nnz,&b->A); CHKERRQ(ierr); 1969 PLogObjectParent(B,b->A); 1970 if (o_nz == PETSC_DEFAULT) o_nz = 0; 1971 ierr = MatCreateSeqBAIJ(PETSC_COMM_SELF,bs,m,N,o_nz,o_nnz,&b->B); CHKERRQ(ierr); 1972 PLogObjectParent(B,b->B); 1973 1974 /* build cache for off array entries formed */ 1975 ierr = StashBuild_Private(&b->stash); CHKERRQ(ierr); 1976 b->donotstash = 0; 1977 b->colmap = 0; 1978 b->garray = 0; 1979 b->roworiented = 1; 1980 1981 /* stuff used in block assembly */ 1982 b->barray = 0; 1983 1984 /* stuff used for matrix vector multiply */ 1985 b->lvec = 0; 1986 b->Mvctx = 0; 1987 1988 /* stuff for MatGetRow() */ 1989 b->rowindices = 0; 1990 b->rowvalues = 0; 1991 b->getrowactive = PETSC_FALSE; 1992 1993 /* hash table stuff */ 1994 b->ht = 0; 1995 b->hd = 0; 1996 b->ht_size = 0; 1997 b->ht_flag = 0; 1998 b->ht_fact = 0; 1999 b->ht_total_ct = 0; 2000 b->ht_insert_ct = 0; 2001 2002 *A = B; 2003 ierr = OptionsHasName(PETSC_NULL,"-mat_use_hash_table",&flg); CHKERRQ(ierr); 2004 if (flg) { 2005 double fact = 1.39; 2006 ierr = MatSetOption(B,MAT_USE_HASH_TABLE); CHKERRQ(ierr); 2007 ierr = OptionsGetDouble(PETSC_NULL,"-mat_use_hash_table",&fact,&flg); CHKERRQ(ierr); 2008 if (fact <= 1.0) fact = 1.39; 2009 ierr = MatMPIBAIJSetHashTableFactor(B,fact); CHKERRQ(ierr); 2010 PLogInfo(0,"MatCreateMPIBAIJ:Hash table Factor used %5.2f\n",fact); 2011 } 2012 PetscFunctionReturn(0); 2013 } 2014 2015 #undef __FUNC__ 2016 #define __FUNC__ "MatConvertSameType_MPIBAIJ" 2017 static int MatConvertSameType_MPIBAIJ(Mat matin,Mat *newmat,int cpvalues) 2018 { 2019 Mat mat; 2020 Mat_MPIBAIJ *a,*oldmat = (Mat_MPIBAIJ *) matin->data; 2021 int ierr, len=0, flg; 2022 2023 PetscFunctionBegin; 2024 *newmat = 0; 2025 PetscHeaderCreate(mat,_p_Mat,struct _MatOps,MAT_COOKIE,MATMPIBAIJ,matin->comm,MatDestroy,MatView); 2026 PLogObjectCreate(mat); 2027 mat->data = (void *) (a = PetscNew(Mat_MPIBAIJ)); CHKPTRQ(a); 2028 PetscMemcpy(mat->ops,&MatOps,sizeof(struct _MatOps)); 2029 mat->ops->destroy = MatDestroy_MPIBAIJ; 2030 mat->ops->view = MatView_MPIBAIJ; 2031 mat->factor = matin->factor; 2032 mat->assembled = PETSC_TRUE; 2033 2034 a->m = mat->m = oldmat->m; 2035 a->n = mat->n = oldmat->n; 2036 a->M = mat->M = oldmat->M; 2037 a->N = mat->N = oldmat->N; 2038 2039 a->bs = oldmat->bs; 2040 a->bs2 = oldmat->bs2; 2041 a->mbs = oldmat->mbs; 2042 a->nbs = oldmat->nbs; 2043 a->Mbs = oldmat->Mbs; 2044 a->Nbs = oldmat->Nbs; 2045 2046 a->rstart = oldmat->rstart; 2047 a->rend = oldmat->rend; 2048 a->cstart = oldmat->cstart; 2049 a->cend = oldmat->cend; 2050 a->size = oldmat->size; 2051 a->rank = oldmat->rank; 2052 mat->insertmode = NOT_SET_VALUES; 2053 a->rowvalues = 0; 2054 a->getrowactive = PETSC_FALSE; 2055 a->barray = 0; 2056 2057 /* hash table stuff */ 2058 a->ht = 0; 2059 a->hd = 0; 2060 a->ht_size = 0; 2061 a->ht_flag = oldmat->ht_flag; 2062 a->ht_fact = oldmat->ht_fact; 2063 a->ht_total_ct = 0; 2064 a->ht_insert_ct = 0; 2065 2066 2067 a->rowners = (int *) PetscMalloc(2*(a->size+2)*sizeof(int)); CHKPTRQ(a->rowners); 2068 PLogObjectMemory(mat,2*(a->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPIBAIJ)); 2069 a->cowners = a->rowners + a->size + 2; 2070 PetscMemcpy(a->rowners,oldmat->rowners,2*(a->size+2)*sizeof(int)); 2071 ierr = StashInitialize_Private(&a->stash); CHKERRQ(ierr); 2072 if (oldmat->colmap) { 2073 a->colmap = (int *) PetscMalloc((a->Nbs)*sizeof(int));CHKPTRQ(a->colmap); 2074 PLogObjectMemory(mat,(a->Nbs)*sizeof(int)); 2075 PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(int)); 2076 } else a->colmap = 0; 2077 if (oldmat->garray && (len = ((Mat_SeqBAIJ *) (oldmat->B->data))->nbs)) { 2078 a->garray = (int *) PetscMalloc(len*sizeof(int)); CHKPTRQ(a->garray); 2079 PLogObjectMemory(mat,len*sizeof(int)); 2080 PetscMemcpy(a->garray,oldmat->garray,len*sizeof(int)); 2081 } else a->garray = 0; 2082 2083 ierr = VecDuplicate(oldmat->lvec,&a->lvec); CHKERRQ(ierr); 2084 PLogObjectParent(mat,a->lvec); 2085 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx); CHKERRQ(ierr); 2086 PLogObjectParent(mat,a->Mvctx); 2087 ierr = MatConvert(oldmat->A,MATSAME,&a->A); CHKERRQ(ierr); 2088 PLogObjectParent(mat,a->A); 2089 ierr = MatConvert(oldmat->B,MATSAME,&a->B); CHKERRQ(ierr); 2090 PLogObjectParent(mat,a->B); 2091 ierr = OptionsHasName(PETSC_NULL,"-help",&flg); CHKERRQ(ierr); 2092 if (flg) { 2093 ierr = MatPrintHelp(mat); CHKERRQ(ierr); 2094 } 2095 *newmat = mat; 2096 PetscFunctionReturn(0); 2097 } 2098 2099 #include "sys.h" 2100 2101 #undef __FUNC__ 2102 #define __FUNC__ "MatLoad_MPIBAIJ" 2103 int MatLoad_MPIBAIJ(Viewer viewer,MatType type,Mat *newmat) 2104 { 2105 Mat A; 2106 int i, nz, ierr, j,rstart, rend, fd; 2107 Scalar *vals,*buf; 2108 MPI_Comm comm = ((PetscObject)viewer)->comm; 2109 MPI_Status status; 2110 int header[4],rank,size,*rowlengths = 0,M,N,m,*rowners,*browners,maxnz,*cols; 2111 int *locrowlens,*sndcounts = 0,*procsnz = 0, jj,*mycols,*ibuf; 2112 int flg,tag = ((PetscObject)viewer)->tag,bs=1,Mbs,mbs,extra_rows; 2113 int *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2114 int dcount,kmax,k,nzcount,tmp; 2115 2116 PetscFunctionBegin; 2117 ierr = OptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,&flg);CHKERRQ(ierr); 2118 2119 MPI_Comm_size(comm,&size); MPI_Comm_rank(comm,&rank); 2120 if (!rank) { 2121 ierr = ViewerBinaryGetDescriptor(viewer,&fd); CHKERRQ(ierr); 2122 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT); CHKERRQ(ierr); 2123 if (header[0] != MAT_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,0,"not matrix object"); 2124 if (header[3] < 0) { 2125 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,1,"Matrix stored in special format, cannot load as MPIBAIJ"); 2126 } 2127 } 2128 2129 ierr = MPI_Bcast(header+1,3,MPI_INT,0,comm);CHKERRQ(ierr); 2130 M = header[1]; N = header[2]; 2131 2132 if (M != N) SETERRQ(PETSC_ERR_SUP,0,"Can only do square matrices"); 2133 2134 /* 2135 This code adds extra rows to make sure the number of rows is 2136 divisible by the blocksize 2137 */ 2138 Mbs = M/bs; 2139 extra_rows = bs - M + bs*(Mbs); 2140 if (extra_rows == bs) extra_rows = 0; 2141 else Mbs++; 2142 if (extra_rows &&!rank) { 2143 PLogInfo(0,"MatLoad_MPIBAIJ:Padding loaded matrix to match blocksize\n"); 2144 } 2145 2146 /* determine ownership of all rows */ 2147 mbs = Mbs/size + ((Mbs % size) > rank); 2148 m = mbs * bs; 2149 rowners = (int *) PetscMalloc(2*(size+2)*sizeof(int)); CHKPTRQ(rowners); 2150 browners = rowners + size + 1; 2151 ierr = MPI_Allgather(&mbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2152 rowners[0] = 0; 2153 for ( i=2; i<=size; i++ ) rowners[i] += rowners[i-1]; 2154 for ( i=0; i<=size; i++ ) browners[i] = rowners[i]*bs; 2155 rstart = rowners[rank]; 2156 rend = rowners[rank+1]; 2157 2158 /* distribute row lengths to all processors */ 2159 locrowlens = (int*) PetscMalloc( (rend-rstart)*bs*sizeof(int) ); CHKPTRQ(locrowlens); 2160 if (!rank) { 2161 rowlengths = (int*) PetscMalloc( (M+extra_rows)*sizeof(int) ); CHKPTRQ(rowlengths); 2162 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT); CHKERRQ(ierr); 2163 for ( i=0; i<extra_rows; i++ ) rowlengths[M+i] = 1; 2164 sndcounts = (int*) PetscMalloc( size*sizeof(int) ); CHKPTRQ(sndcounts); 2165 for ( i=0; i<size; i++ ) sndcounts[i] = browners[i+1] - browners[i]; 2166 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr); 2167 PetscFree(sndcounts); 2168 } else { 2169 ierr = MPI_Scatterv(0,0,0,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT, 0,comm);CHKERRQ(ierr); 2170 } 2171 2172 if (!rank) { 2173 /* calculate the number of nonzeros on each processor */ 2174 procsnz = (int*) PetscMalloc( size*sizeof(int) ); CHKPTRQ(procsnz); 2175 PetscMemzero(procsnz,size*sizeof(int)); 2176 for ( i=0; i<size; i++ ) { 2177 for ( j=rowners[i]*bs; j< rowners[i+1]*bs; j++ ) { 2178 procsnz[i] += rowlengths[j]; 2179 } 2180 } 2181 PetscFree(rowlengths); 2182 2183 /* determine max buffer needed and allocate it */ 2184 maxnz = 0; 2185 for ( i=0; i<size; i++ ) { 2186 maxnz = PetscMax(maxnz,procsnz[i]); 2187 } 2188 cols = (int *) PetscMalloc( maxnz*sizeof(int) ); CHKPTRQ(cols); 2189 2190 /* read in my part of the matrix column indices */ 2191 nz = procsnz[0]; 2192 ibuf = (int *) PetscMalloc( nz*sizeof(int) ); CHKPTRQ(ibuf); 2193 mycols = ibuf; 2194 if (size == 1) nz -= extra_rows; 2195 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT); CHKERRQ(ierr); 2196 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2197 2198 /* read in every ones (except the last) and ship off */ 2199 for ( i=1; i<size-1; i++ ) { 2200 nz = procsnz[i]; 2201 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT); CHKERRQ(ierr); 2202 ierr = MPI_Send(cols,nz,MPI_INT,i,tag,comm);CHKERRQ(ierr); 2203 } 2204 /* read in the stuff for the last proc */ 2205 if ( size != 1 ) { 2206 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2207 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT); CHKERRQ(ierr); 2208 for ( i=0; i<extra_rows; i++ ) cols[nz+i] = M+i; 2209 ierr = MPI_Send(cols,nz+extra_rows,MPI_INT,size-1,tag,comm);CHKERRQ(ierr); 2210 } 2211 PetscFree(cols); 2212 } else { 2213 /* determine buffer space needed for message */ 2214 nz = 0; 2215 for ( i=0; i<m; i++ ) { 2216 nz += locrowlens[i]; 2217 } 2218 ibuf = (int*) PetscMalloc( nz*sizeof(int) ); CHKPTRQ(ibuf); 2219 mycols = ibuf; 2220 /* receive message of column indices*/ 2221 ierr = MPI_Recv(mycols,nz,MPI_INT,0,tag,comm,&status);CHKERRQ(ierr); 2222 ierr = MPI_Get_count(&status,MPI_INT,&maxnz);CHKERRQ(ierr); 2223 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,0,"something is wrong with file"); 2224 } 2225 2226 /* loop over local rows, determining number of off diagonal entries */ 2227 dlens = (int *) PetscMalloc( 2*(rend-rstart+1)*sizeof(int) ); CHKPTRQ(dlens); 2228 odlens = dlens + (rend-rstart); 2229 mask = (int *) PetscMalloc( 3*Mbs*sizeof(int) ); CHKPTRQ(mask); 2230 PetscMemzero(mask,3*Mbs*sizeof(int)); 2231 masked1 = mask + Mbs; 2232 masked2 = masked1 + Mbs; 2233 rowcount = 0; nzcount = 0; 2234 for ( i=0; i<mbs; i++ ) { 2235 dcount = 0; 2236 odcount = 0; 2237 for ( j=0; j<bs; j++ ) { 2238 kmax = locrowlens[rowcount]; 2239 for ( k=0; k<kmax; k++ ) { 2240 tmp = mycols[nzcount++]/bs; 2241 if (!mask[tmp]) { 2242 mask[tmp] = 1; 2243 if (tmp < rstart || tmp >= rend ) masked2[odcount++] = tmp; 2244 else masked1[dcount++] = tmp; 2245 } 2246 } 2247 rowcount++; 2248 } 2249 2250 dlens[i] = dcount; 2251 odlens[i] = odcount; 2252 2253 /* zero out the mask elements we set */ 2254 for ( j=0; j<dcount; j++ ) mask[masked1[j]] = 0; 2255 for ( j=0; j<odcount; j++ ) mask[masked2[j]] = 0; 2256 } 2257 2258 /* create our matrix */ 2259 ierr = MatCreateMPIBAIJ(comm,bs,m,PETSC_DECIDE,M+extra_rows,N+extra_rows,0,dlens,0,odlens,newmat); 2260 CHKERRQ(ierr); 2261 A = *newmat; 2262 MatSetOption(A,MAT_COLUMNS_SORTED); 2263 2264 if (!rank) { 2265 buf = (Scalar *) PetscMalloc( maxnz*sizeof(Scalar) ); CHKPTRQ(buf); 2266 /* read in my part of the matrix numerical values */ 2267 nz = procsnz[0]; 2268 vals = buf; 2269 mycols = ibuf; 2270 if (size == 1) nz -= extra_rows; 2271 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR); CHKERRQ(ierr); 2272 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2273 2274 /* insert into matrix */ 2275 jj = rstart*bs; 2276 for ( i=0; i<m; i++ ) { 2277 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2278 mycols += locrowlens[i]; 2279 vals += locrowlens[i]; 2280 jj++; 2281 } 2282 /* read in other processors (except the last one) and ship out */ 2283 for ( i=1; i<size-1; i++ ) { 2284 nz = procsnz[i]; 2285 vals = buf; 2286 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR); CHKERRQ(ierr); 2287 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 2288 } 2289 /* the last proc */ 2290 if ( size != 1 ){ 2291 nz = procsnz[i] - extra_rows; 2292 vals = buf; 2293 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR); CHKERRQ(ierr); 2294 for ( i=0; i<extra_rows; i++ ) vals[nz+i] = 1.0; 2295 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,A->tag,comm);CHKERRQ(ierr); 2296 } 2297 PetscFree(procsnz); 2298 } else { 2299 /* receive numeric values */ 2300 buf = (Scalar*) PetscMalloc( nz*sizeof(Scalar) ); CHKPTRQ(buf); 2301 2302 /* receive message of values*/ 2303 vals = buf; 2304 mycols = ibuf; 2305 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 2306 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2307 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,0,"something is wrong with file"); 2308 2309 /* insert into matrix */ 2310 jj = rstart*bs; 2311 for ( i=0; i<m; i++ ) { 2312 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2313 mycols += locrowlens[i]; 2314 vals += locrowlens[i]; 2315 jj++; 2316 } 2317 } 2318 PetscFree(locrowlens); 2319 PetscFree(buf); 2320 PetscFree(ibuf); 2321 PetscFree(rowners); 2322 PetscFree(dlens); 2323 PetscFree(mask); 2324 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 2325 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 2326 PetscFunctionReturn(0); 2327 } 2328 2329 2330 2331 #undef __FUNC__ 2332 #define __FUNC__ "MatMPIBAIJSetHashTableFactor" 2333 /*@ 2334 MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2335 2336 Input Parameters: 2337 . mat - the matrix 2338 . fact - factor 2339 2340 Collective on Mat 2341 2342 Notes: 2343 This can also be set by the command line option: -mat_use_hash_table fact 2344 2345 .keywords: matrix, hashtable, factor, HT 2346 2347 .seealso: MatSetOption() 2348 @*/ 2349 int MatMPIBAIJSetHashTableFactor(Mat mat,double fact) 2350 { 2351 Mat_MPIBAIJ *baij; 2352 2353 PetscFunctionBegin; 2354 PetscValidHeaderSpecific(mat,MAT_COOKIE); 2355 if (mat->type != MATMPIBAIJ) { 2356 SETERRQ(PETSC_ERR_ARG_WRONG,1,"Incorrect matrix type. Use MPIBAIJ only."); 2357 } 2358 baij = (Mat_MPIBAIJ*) mat->data; 2359 baij->ht_fact = fact; 2360 PetscFunctionReturn(0); 2361 } 2362