1 #ifdef PETSC_RCS_HEADER 2 static char vcid[] = "$Id: mpibaij.c,v 1.131 1998/07/13 20:45:04 bsmith Exp bsmith $"; 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 extern int MatGetValues_SeqBAIJ(Mat,int,int *,int,int *,Scalar *); 15 16 /* 17 Local utility routine that creates a mapping from the global column 18 number to the local number in the off-diagonal part of the local 19 storage of the matrix. This is done in a non scable way since the 20 length of colmap equals the global matrix length. 21 */ 22 #undef __FUNC__ 23 #define __FUNC__ "CreateColmap_MPIBAIJ_Private" 24 static int CreateColmap_MPIBAIJ_Private(Mat mat) 25 { 26 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 27 Mat_SeqBAIJ *B = (Mat_SeqBAIJ*) baij->B->data; 28 int nbs = B->nbs,i,bs=B->bs;; 29 30 PetscFunctionBegin; 31 baij->colmap = (int *) PetscMalloc((baij->Nbs+1)*sizeof(int));CHKPTRQ(baij->colmap); 32 PLogObjectMemory(mat,baij->Nbs*sizeof(int)); 33 PetscMemzero(baij->colmap,baij->Nbs*sizeof(int)); 34 for ( i=0; i<nbs; i++ ) baij->colmap[baij->garray[i]] = i*bs+1; 35 PetscFunctionReturn(0); 36 } 37 38 #define CHUNKSIZE 10 39 40 #define MatSetValues_SeqBAIJ_A_Private(row,col,value,addv) \ 41 { \ 42 \ 43 brow = row/bs; \ 44 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 45 rmax = aimax[brow]; nrow = ailen[brow]; \ 46 bcol = col/bs; \ 47 ridx = row % bs; cidx = col % bs; \ 48 low = 0; high = nrow; \ 49 while (high-low > 3) { \ 50 t = (low+high)/2; \ 51 if (rp[t] > bcol) high = t; \ 52 else low = t; \ 53 } \ 54 for ( _i=low; _i<high; _i++ ) { \ 55 if (rp[_i] > bcol) break; \ 56 if (rp[_i] == bcol) { \ 57 bap = ap + bs2*_i + bs*cidx + ridx; \ 58 if (addv == ADD_VALUES) *bap += value; \ 59 else *bap = value; \ 60 goto a_noinsert; \ 61 } \ 62 } \ 63 if (a->nonew == 1) goto a_noinsert; \ 64 else if (a->nonew == -1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Inserting a new nonzero into matrix"); \ 65 if (nrow >= rmax) { \ 66 /* there is no extra room in row, therefore enlarge */ \ 67 int new_nz = ai[a->mbs] + CHUNKSIZE,len,*new_i,*new_j; \ 68 Scalar *new_a; \ 69 \ 70 if (a->nonew == -2) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Inserting a new nonzero in the matrix"); \ 71 \ 72 /* malloc new storage space */ \ 73 len = new_nz*(sizeof(int)+bs2*sizeof(Scalar))+(a->mbs+1)*sizeof(int); \ 74 new_a = (Scalar *) PetscMalloc( len ); CHKPTRQ(new_a); \ 75 new_j = (int *) (new_a + bs2*new_nz); \ 76 new_i = new_j + new_nz; \ 77 \ 78 /* copy over old data into new slots */ \ 79 for ( ii=0; ii<brow+1; ii++ ) {new_i[ii] = ai[ii];} \ 80 for ( ii=brow+1; ii<a->mbs+1; ii++ ) {new_i[ii] = ai[ii]+CHUNKSIZE;} \ 81 PetscMemcpy(new_j,aj,(ai[brow]+nrow)*sizeof(int)); \ 82 len = (new_nz - CHUNKSIZE - ai[brow] - nrow); \ 83 PetscMemcpy(new_j+ai[brow]+nrow+CHUNKSIZE,aj+ai[brow]+nrow, \ 84 len*sizeof(int)); \ 85 PetscMemcpy(new_a,aa,(ai[brow]+nrow)*bs2*sizeof(Scalar)); \ 86 PetscMemzero(new_a+bs2*(ai[brow]+nrow),bs2*CHUNKSIZE*sizeof(Scalar)); \ 87 PetscMemcpy(new_a+bs2*(ai[brow]+nrow+CHUNKSIZE), \ 88 aa+bs2*(ai[brow]+nrow),bs2*len*sizeof(Scalar)); \ 89 /* free up old matrix storage */ \ 90 PetscFree(a->a); \ 91 if (!a->singlemalloc) {PetscFree(a->i);PetscFree(a->j);} \ 92 aa = a->a = new_a; ai = a->i = new_i; aj = a->j = new_j; \ 93 a->singlemalloc = 1; \ 94 \ 95 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 96 rmax = aimax[brow] = aimax[brow] + CHUNKSIZE; \ 97 PLogObjectMemory(A,CHUNKSIZE*(sizeof(int) + bs2*sizeof(Scalar))); \ 98 a->maxnz += bs2*CHUNKSIZE; \ 99 a->reallocs++; \ 100 a->nz++; \ 101 } \ 102 N = nrow++ - 1; \ 103 /* shift up all the later entries in this row */ \ 104 for ( ii=N; ii>=_i; ii-- ) { \ 105 rp[ii+1] = rp[ii]; \ 106 PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(Scalar)); \ 107 } \ 108 if (N>=_i) PetscMemzero(ap+bs2*_i,bs2*sizeof(Scalar)); \ 109 rp[_i] = bcol; \ 110 ap[bs2*_i + bs*cidx + ridx] = value; \ 111 a_noinsert:; \ 112 ailen[brow] = nrow; \ 113 } 114 115 #define MatSetValues_SeqBAIJ_B_Private(row,col,value,addv) \ 116 { \ 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 else if (b->nonew == -1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Inserting a new nonzero into matrix"); \ 140 if (nrow >= rmax) { \ 141 /* there is no extra room in row, therefore enlarge */ \ 142 int new_nz = bi[b->mbs] + CHUNKSIZE,len,*new_i,*new_j; \ 143 Scalar *new_a; \ 144 \ 145 if (b->nonew == -2) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Inserting a new nonzero in the matrix"); \ 146 \ 147 /* malloc new storage space */ \ 148 len = new_nz*(sizeof(int)+bs2*sizeof(Scalar))+(b->mbs+1)*sizeof(int); \ 149 new_a = (Scalar *) PetscMalloc( len ); CHKPTRQ(new_a); \ 150 new_j = (int *) (new_a + bs2*new_nz); \ 151 new_i = new_j + new_nz; \ 152 \ 153 /* copy over old data into new slots */ \ 154 for ( ii=0; ii<brow+1; ii++ ) {new_i[ii] = bi[ii];} \ 155 for ( ii=brow+1; ii<b->mbs+1; ii++ ) {new_i[ii] = bi[ii]+CHUNKSIZE;} \ 156 PetscMemcpy(new_j,bj,(bi[brow]+nrow)*sizeof(int)); \ 157 len = (new_nz - CHUNKSIZE - bi[brow] - nrow); \ 158 PetscMemcpy(new_j+bi[brow]+nrow+CHUNKSIZE,bj+bi[brow]+nrow, \ 159 len*sizeof(int)); \ 160 PetscMemcpy(new_a,ba,(bi[brow]+nrow)*bs2*sizeof(Scalar)); \ 161 PetscMemzero(new_a+bs2*(bi[brow]+nrow),bs2*CHUNKSIZE*sizeof(Scalar)); \ 162 PetscMemcpy(new_a+bs2*(bi[brow]+nrow+CHUNKSIZE), \ 163 ba+bs2*(bi[brow]+nrow),bs2*len*sizeof(Scalar)); \ 164 /* free up old matrix storage */ \ 165 PetscFree(b->a); \ 166 if (!b->singlemalloc) {PetscFree(b->i);PetscFree(b->j);} \ 167 ba = b->a = new_a; bi = b->i = new_i; bj = b->j = new_j; \ 168 b->singlemalloc = 1; \ 169 \ 170 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 171 rmax = bimax[brow] = bimax[brow] + CHUNKSIZE; \ 172 PLogObjectMemory(B,CHUNKSIZE*(sizeof(int) + bs2*sizeof(Scalar))); \ 173 b->maxnz += bs2*CHUNKSIZE; \ 174 b->reallocs++; \ 175 b->nz++; \ 176 } \ 177 N = nrow++ - 1; \ 178 /* shift up all the later entries in this row */ \ 179 for ( ii=N; ii>=_i; ii-- ) { \ 180 rp[ii+1] = rp[ii]; \ 181 PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(Scalar)); \ 182 } \ 183 if (N>=_i) PetscMemzero(ap+bs2*_i,bs2*sizeof(Scalar)); \ 184 rp[_i] = bcol; \ 185 ap[bs2*_i + bs*cidx + ridx] = value; \ 186 b_noinsert:; \ 187 bilen[brow] = nrow; \ 188 } 189 190 #undef __FUNC__ 191 #define __FUNC__ "MatSetValues_MPIBAIJ" 192 int MatSetValues_MPIBAIJ(Mat mat,int m,int *im,int n,int *in,Scalar *v,InsertMode addv) 193 { 194 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 195 Scalar value; 196 int ierr,i,j,row,col; 197 int roworiented = baij->roworiented,rstart_orig=baij->rstart_bs ; 198 int rend_orig=baij->rend_bs,cstart_orig=baij->cstart_bs; 199 int cend_orig=baij->cend_bs,bs=baij->bs; 200 201 /* Some Variables required in the macro */ 202 Mat A = baij->A; 203 Mat_SeqBAIJ *a = (Mat_SeqBAIJ *) (A)->data; 204 int *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 205 Scalar *aa=a->a; 206 207 Mat B = baij->B; 208 Mat_SeqBAIJ *b = (Mat_SeqBAIJ *) (B)->data; 209 int *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 210 Scalar *ba=b->a; 211 212 int *rp,ii,nrow,_i,rmax,N,brow,bcol; 213 int low,high,t,ridx,cidx,bs2=a->bs2; 214 Scalar *ap,*bap; 215 216 PetscFunctionBegin; 217 for ( i=0; i<m; i++ ) { 218 #if defined(USE_PETSC_BOPT_g) 219 if (im[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Negative row"); 220 if (im[i] >= baij->M) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Row too large"); 221 #endif 222 if (im[i] >= rstart_orig && im[i] < rend_orig) { 223 row = im[i] - rstart_orig; 224 for ( j=0; j<n; j++ ) { 225 if (in[j] >= cstart_orig && in[j] < cend_orig){ 226 col = in[j] - cstart_orig; 227 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 228 MatSetValues_SeqBAIJ_A_Private(row,col,value,addv); 229 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 230 } 231 #if defined(USE_PETSC_BOPT_g) 232 else if (in[j] < 0) {SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Negative column");} 233 else if (in[j] >= baij->N) {SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Col too large");} 234 #endif 235 else { 236 if (mat->was_assembled) { 237 if (!baij->colmap) { 238 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 239 } 240 col = baij->colmap[in[j]/bs] - 1 + in[j]%bs; 241 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 242 ierr = DisAssemble_MPIBAIJ(mat); CHKERRQ(ierr); 243 col = in[j]; 244 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 245 B = baij->B; 246 b = (Mat_SeqBAIJ *) (B)->data; 247 bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 248 ba=b->a; 249 } 250 } else col = in[j]; 251 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 252 MatSetValues_SeqBAIJ_B_Private(row,col,value,addv); 253 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 254 } 255 } 256 } else { 257 if (roworiented && !baij->donotstash) { 258 ierr = StashValues_Private(&baij->stash,im[i],n,in,v+i*n,addv);CHKERRQ(ierr); 259 } else { 260 if (!baij->donotstash) { 261 row = im[i]; 262 for ( j=0; j<n; j++ ) { 263 ierr = StashValues_Private(&baij->stash,row,1,in+j,v+i+j*m,addv);CHKERRQ(ierr); 264 } 265 } 266 } 267 } 268 } 269 PetscFunctionReturn(0); 270 } 271 272 extern int MatSetValuesBlocked_SeqBAIJ(Mat,int,int*,int,int*,Scalar*,InsertMode); 273 #undef __FUNC__ 274 #define __FUNC__ "MatSetValuesBlocked_MPIBAIJ" 275 int MatSetValuesBlocked_MPIBAIJ(Mat mat,int m,int *im,int n,int *in,Scalar *v,InsertMode addv) 276 { 277 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 278 Scalar *value,*barray=baij->barray; 279 int ierr,i,j,ii,jj,row,col,k,l; 280 int roworiented = baij->roworiented,rstart=baij->rstart ; 281 int rend=baij->rend,cstart=baij->cstart,stepval; 282 int cend=baij->cend,bs=baij->bs,bs2=baij->bs2; 283 284 if(!barray) { 285 baij->barray = barray = (Scalar*) PetscMalloc(bs2*sizeof(Scalar)); CHKPTRQ(barray); 286 } 287 288 if (roworiented) { 289 stepval = (n-1)*bs; 290 } else { 291 stepval = (m-1)*bs; 292 } 293 for ( i=0; i<m; i++ ) { 294 #if defined(USE_PETSC_BOPT_g) 295 if (im[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Negative row"); 296 if (im[i] >= baij->Mbs) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Row too large"); 297 #endif 298 if (im[i] >= rstart && im[i] < rend) { 299 row = im[i] - rstart; 300 for ( j=0; j<n; j++ ) { 301 /* If NumCol = 1 then a copy is not required */ 302 if ((roworiented) && (n == 1)) { 303 barray = v + i*bs2; 304 } else if((!roworiented) && (m == 1)) { 305 barray = v + j*bs2; 306 } else { /* Here a copy is required */ 307 if (roworiented) { 308 value = v + i*(stepval+bs)*bs + j*bs; 309 } else { 310 value = v + j*(stepval+bs)*bs + i*bs; 311 } 312 for ( ii=0; ii<bs; ii++,value+=stepval ) { 313 for (jj=0; jj<bs; jj++ ) { 314 *barray++ = *value++; 315 } 316 } 317 barray -=bs2; 318 } 319 320 if (in[j] >= cstart && in[j] < cend){ 321 col = in[j] - cstart; 322 ierr = MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 323 } 324 #if defined(USE_PETSC_BOPT_g) 325 else if (in[j] < 0) {SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Negative column");} 326 else if (in[j] >= baij->Nbs) {SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Column too large");} 327 #endif 328 else { 329 if (mat->was_assembled) { 330 if (!baij->colmap) { 331 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 332 } 333 334 #if defined(USE_PETSC_BOPT_g) 335 if ((baij->colmap[in[j]] - 1) % bs) {SETERRQ(PETSC_ERR_PLIB,0,"Incorrect colmap");} 336 #endif 337 col = (baij->colmap[in[j]] - 1)/bs; 338 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 339 ierr = DisAssemble_MPIBAIJ(mat); CHKERRQ(ierr); 340 col = in[j]; 341 } 342 } 343 else col = in[j]; 344 ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr); 345 } 346 } 347 } else { 348 if (!baij->donotstash) { 349 if (roworiented ) { 350 row = im[i]*bs; 351 value = v + i*(stepval+bs)*bs; 352 for ( j=0; j<bs; j++,row++ ) { 353 for ( k=0; k<n; k++ ) { 354 for ( col=in[k]*bs,l=0; l<bs; l++,col++) { 355 ierr = StashValues_Private(&baij->stash,row,1,&col,value++,addv);CHKERRQ(ierr); 356 } 357 } 358 } 359 } else { 360 for ( j=0; j<n; j++ ) { 361 value = v + j*(stepval+bs)*bs + i*bs; 362 col = in[j]*bs; 363 for ( k=0; k<bs; k++,col++,value+=stepval) { 364 for ( row = im[i]*bs,l=0; l<bs; l++,row++) { 365 ierr = StashValues_Private(&baij->stash,row,1,&col,value++,addv);CHKERRQ(ierr); 366 } 367 } 368 } 369 } 370 } 371 } 372 } 373 PetscFunctionReturn(0); 374 } 375 #include <math.h> 376 #define HASH_KEY 0.6180339887 377 /* #define HASH1(size,key) ((int)((size)*fmod(((key)*HASH_KEY),1))) */ 378 #define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(int)((size)*(tmp-(int)tmp))) 379 /* #define HASH(size,key,tmp) ((int)((size)*fmod(((key)*HASH_KEY),1))) */ 380 #undef __FUNC__ 381 #define __FUNC__ "MatSetValues_MPIBAIJ_HT" 382 int MatSetValues_MPIBAIJ_HT(Mat mat,int m,int *im,int n,int *in,Scalar *v,InsertMode addv) 383 { 384 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 385 int ierr,i,j,row,col; 386 int roworiented = baij->roworiented,rstart_orig=baij->rstart_bs ; 387 int rend_orig=baij->rend_bs,Nbs=baij->Nbs; 388 int h1,key,size=baij->ht_size,bs=baij->bs,*HT=baij->ht,idx; 389 double tmp; 390 Scalar ** HD = baij->hd,value; 391 #if defined(USE_PETSC_BOPT_g) 392 int total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 393 #endif 394 395 PetscFunctionBegin; 396 397 for ( i=0; i<m; i++ ) { 398 #if defined(USE_PETSC_BOPT_g) 399 if (im[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Negative row"); 400 if (im[i] >= baij->M) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Row too large"); 401 #endif 402 row = im[i]; 403 if (row >= rstart_orig && row < rend_orig) { 404 for ( j=0; j<n; j++ ) { 405 col = in[j]; 406 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 407 /* Look up into the Hash Table */ 408 key = (row/bs)*Nbs+(col/bs)+1; 409 h1 = HASH(size,key,tmp); 410 411 412 idx = h1; 413 #if defined(USE_PETSC_BOPT_g) 414 insert_ct++; 415 total_ct++; 416 if (HT[idx] != key) { 417 for ( idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++); 418 if (idx == size) { 419 for ( idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++); 420 if (idx == h1) { 421 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"(row,col) has no entry in the hash table"); 422 } 423 } 424 } 425 #else 426 if (HT[idx] != key) { 427 for ( idx=h1; (idx<size) && (HT[idx]!=key); idx++); 428 if (idx == size) { 429 for ( idx=0; (idx<h1) && (HT[idx]!=key); idx++); 430 if (idx == h1) { 431 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"(row,col) has no entry in the hash table"); 432 } 433 } 434 } 435 #endif 436 /* A HASH table entry is found, so insert the values at the correct address */ 437 if (addv == ADD_VALUES) *(HD[idx]+ (col % bs)*bs + (row % bs)) += value; 438 else *(HD[idx]+ (col % bs)*bs + (row % bs)) = value; 439 } 440 } else { 441 if (roworiented && !baij->donotstash) { 442 ierr = StashValues_Private(&baij->stash,im[i],n,in,v+i*n,addv);CHKERRQ(ierr); 443 } else { 444 if (!baij->donotstash) { 445 row = im[i]; 446 for ( j=0; j<n; j++ ) { 447 ierr = StashValues_Private(&baij->stash,row,1,in+j,v+i+j*m,addv);CHKERRQ(ierr); 448 } 449 } 450 } 451 } 452 } 453 #if defined(USE_PETSC_BOPT_g) 454 baij->ht_total_ct = total_ct; 455 baij->ht_insert_ct = insert_ct; 456 #endif 457 PetscFunctionReturn(0); 458 } 459 460 #undef __FUNC__ 461 #define __FUNC__ "MatSetValuesBlocked_MPIBAIJ_HT" 462 int MatSetValuesBlocked_MPIBAIJ_HT(Mat mat,int m,int *im,int n,int *in,Scalar *v,InsertMode addv) 463 { 464 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 465 int ierr,i,j,ii,jj,row,col,k,l; 466 int roworiented = baij->roworiented,rstart=baij->rstart ; 467 int rend=baij->rend,stepval,bs=baij->bs,bs2=baij->bs2; 468 int h1,key,size=baij->ht_size,idx,*HT=baij->ht,Nbs=baij->Nbs; 469 double tmp; 470 Scalar ** HD = baij->hd,*value,*v_t,*baij_a; 471 #if defined(USE_PETSC_BOPT_g) 472 int total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct; 473 #endif 474 475 PetscFunctionBegin; 476 477 if (roworiented) { 478 stepval = (n-1)*bs; 479 } else { 480 stepval = (m-1)*bs; 481 } 482 for ( i=0; i<m; i++ ) { 483 #if defined(USE_PETSC_BOPT_g) 484 if (im[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Negative row"); 485 if (im[i] >= baij->Mbs) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Row too large"); 486 #endif 487 row = im[i]; 488 v_t = v + i*bs2; 489 if (row >= rstart && row < rend) { 490 for ( j=0; j<n; j++ ) { 491 col = in[j]; 492 493 /* Look up into the Hash Table */ 494 key = row*Nbs+col+1; 495 h1 = HASH(size,key,tmp); 496 497 idx = h1; 498 #if defined(USE_PETSC_BOPT_g) 499 total_ct++; 500 insert_ct++; 501 if (HT[idx] != key) { 502 for ( idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++); 503 if (idx == size) { 504 for ( idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++); 505 if (idx == h1) { 506 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"(row,col) has no entry in the hash table"); 507 } 508 } 509 } 510 #else 511 if (HT[idx] != key) { 512 for ( idx=h1; (idx<size) && (HT[idx]!=key); idx++); 513 if (idx == size) { 514 for ( idx=0; (idx<h1) && (HT[idx]!=key); idx++); 515 if (idx == h1) { 516 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"(row,col) has no entry in the hash table"); 517 } 518 } 519 } 520 #endif 521 baij_a = HD[idx]; 522 if (roworiented) { 523 /*value = v + i*(stepval+bs)*bs + j*bs;*/ 524 /* value = v + (i*(stepval+bs)+j)*bs; */ 525 value = v_t; 526 v_t += bs; 527 if (addv == ADD_VALUES) { 528 for ( ii=0; ii<bs; ii++,value+=stepval) { 529 for ( jj=ii; jj<bs2; jj+=bs ) { 530 baij_a[jj] += *value++; 531 } 532 } 533 } else { 534 for ( ii=0; ii<bs; ii++,value+=stepval) { 535 for ( jj=ii; jj<bs2; jj+=bs ) { 536 baij_a[jj] = *value++; 537 } 538 } 539 } 540 } else { 541 value = v + j*(stepval+bs)*bs + i*bs; 542 if (addv == ADD_VALUES) { 543 for ( ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs ) { 544 for ( jj=0; jj<bs; jj++ ) { 545 baij_a[jj] += *value++; 546 } 547 } 548 } else { 549 for ( ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs ) { 550 for ( jj=0; jj<bs; jj++ ) { 551 baij_a[jj] = *value++; 552 } 553 } 554 } 555 } 556 } 557 } else { 558 if (!baij->donotstash) { 559 if (roworiented ) { 560 row = im[i]*bs; 561 value = v + i*(stepval+bs)*bs; 562 for ( j=0; j<bs; j++,row++ ) { 563 for ( k=0; k<n; k++ ) { 564 for ( col=in[k]*bs,l=0; l<bs; l++,col++) { 565 ierr = StashValues_Private(&baij->stash,row,1,&col,value++,addv);CHKERRQ(ierr); 566 } 567 } 568 } 569 } else { 570 for ( j=0; j<n; j++ ) { 571 value = v + j*(stepval+bs)*bs + i*bs; 572 col = in[j]*bs; 573 for ( k=0; k<bs; k++,col++,value+=stepval) { 574 for ( row = im[i]*bs,l=0; l<bs; l++,row++) { 575 ierr = StashValues_Private(&baij->stash,row,1,&col,value++,addv);CHKERRQ(ierr); 576 } 577 } 578 } 579 } 580 } 581 } 582 } 583 #if defined(USE_PETSC_BOPT_g) 584 baij->ht_total_ct = total_ct; 585 baij->ht_insert_ct = insert_ct; 586 #endif 587 PetscFunctionReturn(0); 588 } 589 590 #undef __FUNC__ 591 #define __FUNC__ "MatGetValues_MPIBAIJ" 592 int MatGetValues_MPIBAIJ(Mat mat,int m,int *idxm,int n,int *idxn,Scalar *v) 593 { 594 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 595 int bs=baij->bs,ierr,i,j, bsrstart = baij->rstart*bs, bsrend = baij->rend*bs; 596 int bscstart = baij->cstart*bs, bscend = baij->cend*bs,row,col; 597 598 PetscFunctionBegin; 599 for ( i=0; i<m; i++ ) { 600 if (idxm[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Negative row"); 601 if (idxm[i] >= baij->M) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Row too large"); 602 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 603 row = idxm[i] - bsrstart; 604 for ( j=0; j<n; j++ ) { 605 if (idxn[j] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Negative column"); 606 if (idxn[j] >= baij->N) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Column too large"); 607 if (idxn[j] >= bscstart && idxn[j] < bscend){ 608 col = idxn[j] - bscstart; 609 ierr = MatGetValues_SeqBAIJ(baij->A,1,&row,1,&col,v+i*n+j); CHKERRQ(ierr); 610 } else { 611 if (!baij->colmap) { 612 ierr = CreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr); 613 } 614 if((baij->colmap[idxn[j]/bs]-1 < 0) || 615 (baij->garray[(baij->colmap[idxn[j]/bs]-1)/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 616 else { 617 col = (baij->colmap[idxn[j]/bs]-1) + idxn[j]%bs; 618 ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j); CHKERRQ(ierr); 619 } 620 } 621 } 622 } else { 623 SETERRQ(PETSC_ERR_SUP,0,"Only local values currently supported"); 624 } 625 } 626 PetscFunctionReturn(0); 627 } 628 629 #undef __FUNC__ 630 #define __FUNC__ "MatNorm_MPIBAIJ" 631 int MatNorm_MPIBAIJ(Mat mat,NormType type,double *norm) 632 { 633 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 634 Mat_SeqBAIJ *amat = (Mat_SeqBAIJ*) baij->A->data, *bmat = (Mat_SeqBAIJ*) baij->B->data; 635 int ierr, i,bs2=baij->bs2; 636 double sum = 0.0; 637 Scalar *v; 638 639 PetscFunctionBegin; 640 if (baij->size == 1) { 641 ierr = MatNorm(baij->A,type,norm); CHKERRQ(ierr); 642 } else { 643 if (type == NORM_FROBENIUS) { 644 v = amat->a; 645 for (i=0; i<amat->nz*bs2; i++ ) { 646 #if defined(USE_PETSC_COMPLEX) 647 sum += PetscReal(PetscConj(*v)*(*v)); v++; 648 #else 649 sum += (*v)*(*v); v++; 650 #endif 651 } 652 v = bmat->a; 653 for (i=0; i<bmat->nz*bs2; i++ ) { 654 #if defined(USE_PETSC_COMPLEX) 655 sum += PetscReal(PetscConj(*v)*(*v)); v++; 656 #else 657 sum += (*v)*(*v); v++; 658 #endif 659 } 660 ierr = MPI_Allreduce(&sum,norm,1,MPI_DOUBLE,MPI_SUM,mat->comm);CHKERRQ(ierr); 661 *norm = sqrt(*norm); 662 } else { 663 SETERRQ(PETSC_ERR_SUP,0,"No support for this norm yet"); 664 } 665 } 666 PetscFunctionReturn(0); 667 } 668 669 #undef __FUNC__ 670 #define __FUNC__ "MatAssemblyBegin_MPIBAIJ" 671 int MatAssemblyBegin_MPIBAIJ(Mat mat,MatAssemblyType mode) 672 { 673 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 674 MPI_Comm comm = mat->comm; 675 int size = baij->size, *owners = baij->rowners,bs=baij->bs; 676 int rank = baij->rank,tag = mat->tag, *owner,*starts,count,ierr; 677 MPI_Request *send_waits,*recv_waits; 678 int *nprocs,i,j,idx,*procs,nsends,nreceives,nmax,*work; 679 InsertMode addv; 680 Scalar *rvalues,*svalues; 681 682 PetscFunctionBegin; 683 if (baij->donotstash) { 684 baij->svalues = 0; baij->rvalues = 0; 685 baij->nsends = 0; baij->nrecvs = 0; 686 baij->send_waits = 0; baij->recv_waits = 0; 687 baij->rmax = 0; 688 PetscFunctionReturn(0); 689 } 690 691 /* make sure all processors are either in INSERTMODE or ADDMODE */ 692 ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,comm);CHKERRQ(ierr); 693 if (addv == (ADD_VALUES|INSERT_VALUES)) { 694 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Some processors inserted others added"); 695 } 696 mat->insertmode = addv; /* in case this processor had no cache */ 697 698 /* first count number of contributors to each processor */ 699 nprocs = (int *) PetscMalloc( 2*size*sizeof(int) ); CHKPTRQ(nprocs); 700 PetscMemzero(nprocs,2*size*sizeof(int)); procs = nprocs + size; 701 owner = (int *) PetscMalloc( (baij->stash.n+1)*sizeof(int) ); CHKPTRQ(owner); 702 for ( i=0; i<baij->stash.n; i++ ) { 703 idx = baij->stash.idx[i]; 704 for ( j=0; j<size; j++ ) { 705 if (idx >= owners[j]*bs && idx < owners[j+1]*bs) { 706 nprocs[j]++; procs[j] = 1; owner[i] = j; break; 707 } 708 } 709 } 710 nsends = 0; for ( i=0; i<size; i++ ) { nsends += procs[i];} 711 712 /* inform other processors of number of messages and max length*/ 713 work = (int *) PetscMalloc( size*sizeof(int) ); CHKPTRQ(work); 714 ierr = MPI_Allreduce(procs, work,size,MPI_INT,MPI_SUM,comm);CHKERRQ(ierr); 715 nreceives = work[rank]; 716 ierr = MPI_Allreduce( nprocs, work,size,MPI_INT,MPI_MAX,comm);CHKERRQ(ierr); 717 nmax = work[rank]; 718 PetscFree(work); 719 720 /* post receives: 721 1) each message will consist of ordered pairs 722 (global index,value) we store the global index as a double 723 to simplify the message passing. 724 2) since we don't know how long each individual message is we 725 allocate the largest needed buffer for each receive. Potentially 726 this is a lot of wasted space. 727 728 729 This could be done better. 730 */ 731 rvalues = (Scalar *) PetscMalloc(3*(nreceives+1)*(nmax+1)*sizeof(Scalar));CHKPTRQ(rvalues); 732 recv_waits = (MPI_Request *) PetscMalloc((nreceives+1)*sizeof(MPI_Request));CHKPTRQ(recv_waits); 733 for ( i=0; i<nreceives; i++ ) { 734 ierr = MPI_Irecv(rvalues+3*nmax*i,3*nmax,MPIU_SCALAR,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 735 } 736 737 /* do sends: 738 1) starts[i] gives the starting index in svalues for stuff going to 739 the ith processor 740 */ 741 svalues = (Scalar *) PetscMalloc(3*(baij->stash.n+1)*sizeof(Scalar));CHKPTRQ(svalues); 742 send_waits = (MPI_Request *) PetscMalloc((nsends+1)*sizeof(MPI_Request));CHKPTRQ(send_waits); 743 starts = (int *) PetscMalloc( size*sizeof(int) ); CHKPTRQ(starts); 744 starts[0] = 0; 745 for ( i=1; i<size; i++ ) { starts[i] = starts[i-1] + nprocs[i-1];} 746 for ( i=0; i<baij->stash.n; i++ ) { 747 svalues[3*starts[owner[i]]] = (Scalar) baij->stash.idx[i]; 748 svalues[3*starts[owner[i]]+1] = (Scalar) baij->stash.idy[i]; 749 svalues[3*(starts[owner[i]]++)+2] = baij->stash.array[i]; 750 } 751 PetscFree(owner); 752 starts[0] = 0; 753 for ( i=1; i<size; i++ ) { starts[i] = starts[i-1] + nprocs[i-1];} 754 count = 0; 755 for ( i=0; i<size; i++ ) { 756 if (procs[i]) { 757 ierr = MPI_Isend(svalues+3*starts[i],3*nprocs[i],MPIU_SCALAR,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 758 } 759 } 760 PetscFree(starts); PetscFree(nprocs); 761 762 /* Free cache space */ 763 PLogInfo(baij->A,"MatAssemblyBegin_MPIBAIJ:Number of off-processor values %d\n",baij->stash.n); 764 ierr = StashDestroy_Private(&baij->stash); CHKERRQ(ierr); 765 766 baij->svalues = svalues; baij->rvalues = rvalues; 767 baij->nsends = nsends; baij->nrecvs = nreceives; 768 baij->send_waits = send_waits; baij->recv_waits = recv_waits; 769 baij->rmax = nmax; 770 771 PetscFunctionReturn(0); 772 } 773 774 /* 775 Creates the hash table, and sets the table 776 This table is created only once. 777 If new entried need to be added to the matrix 778 then the hash table has to be destroyed and 779 recreated. 780 */ 781 #undef __FUNC__ 782 #define __FUNC__ "MatCreateHashTable_MPIBAIJ_Private" 783 int MatCreateHashTable_MPIBAIJ_Private(Mat mat,double factor) 784 { 785 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 786 Mat A = baij->A, B=baij->B; 787 Mat_SeqBAIJ *a=(Mat_SeqBAIJ *)A->data, *b=(Mat_SeqBAIJ *)B->data; 788 int i,j,k,nz=a->nz+b->nz,h1,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j; 789 int size,bs2=baij->bs2,rstart=baij->rstart; 790 int cstart=baij->cstart,*garray=baij->garray,row,col,Nbs=baij->Nbs; 791 int *HT,key; 792 Scalar **HD; 793 double tmp; 794 #if defined(USE_PETSC_BOPT_g) 795 int ct=0,max=0; 796 #endif 797 798 PetscFunctionBegin; 799 baij->ht_size=(int)(factor*nz); 800 size = baij->ht_size; 801 802 if (baij->ht) { 803 PetscFunctionReturn(0); 804 } 805 806 /* Allocate Memory for Hash Table */ 807 baij->hd = (Scalar**)PetscMalloc((size)*(sizeof(int)+sizeof(Scalar*))+1); CHKPTRQ(baij->hd); 808 baij->ht = (int*)(baij->hd + size); 809 HD = baij->hd; 810 HT = baij->ht; 811 812 813 PetscMemzero(HD,size*(sizeof(int)+sizeof(Scalar*))); 814 815 816 /* Loop Over A */ 817 for ( i=0; i<a->mbs; i++ ) { 818 for ( j=ai[i]; j<ai[i+1]; j++ ) { 819 row = i+rstart; 820 col = aj[j]+cstart; 821 822 key = row*Nbs + col + 1; 823 h1 = HASH(size,key,tmp); 824 for ( k=0; k<size; k++ ){ 825 if (HT[(h1+k)%size] == 0.0) { 826 HT[(h1+k)%size] = key; 827 HD[(h1+k)%size] = a->a + j*bs2; 828 break; 829 #if defined(USE_PETSC_BOPT_g) 830 } else { 831 ct++; 832 #endif 833 } 834 } 835 #if defined(USE_PETSC_BOPT_g) 836 if (k> max) max = k; 837 #endif 838 } 839 } 840 /* Loop Over B */ 841 for ( i=0; i<b->mbs; i++ ) { 842 for ( j=bi[i]; j<bi[i+1]; j++ ) { 843 row = i+rstart; 844 col = garray[bj[j]]; 845 key = row*Nbs + col + 1; 846 h1 = HASH(size,key,tmp); 847 for ( k=0; k<size; k++ ){ 848 if (HT[(h1+k)%size] == 0.0) { 849 HT[(h1+k)%size] = key; 850 HD[(h1+k)%size] = b->a + j*bs2; 851 break; 852 #if defined(USE_PETSC_BOPT_g) 853 } else { 854 ct++; 855 #endif 856 } 857 } 858 #if defined(USE_PETSC_BOPT_g) 859 if (k> max) max = k; 860 #endif 861 } 862 } 863 864 /* Print Summary */ 865 #if defined(USE_PETSC_BOPT_g) 866 for ( i=0,j=0; i<size; i++) 867 if (HT[i]) {j++;} 868 PLogInfo(0,"MatCreateHashTable_MPIBAIJ_Private: Average Search = %5.2f,max search = %d\n", 869 (j== 0)? 0.0:((double)(ct+j))/j,max); 870 #endif 871 PetscFunctionReturn(0); 872 } 873 874 #undef __FUNC__ 875 #define __FUNC__ "MatAssemblyEnd_MPIBAIJ" 876 int MatAssemblyEnd_MPIBAIJ(Mat mat,MatAssemblyType mode) 877 { 878 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 879 MPI_Status *send_status,recv_status; 880 int imdex,nrecvs = baij->nrecvs, count = nrecvs, i, n, ierr; 881 int bs=baij->bs,row,col,other_disassembled; 882 Scalar *values,val; 883 InsertMode addv = mat->insertmode; 884 885 PetscFunctionBegin; 886 /* wait on receives */ 887 while (count) { 888 ierr = MPI_Waitany(nrecvs,baij->recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 889 /* unpack receives into our local space */ 890 values = baij->rvalues + 3*imdex*baij->rmax; 891 ierr = MPI_Get_count(&recv_status,MPIU_SCALAR,&n);CHKERRQ(ierr); 892 n = n/3; 893 for ( i=0; i<n; i++ ) { 894 row = (int) PetscReal(values[3*i]) - baij->rstart*bs; 895 col = (int) PetscReal(values[3*i+1]); 896 val = values[3*i+2]; 897 if (col >= baij->cstart*bs && col < baij->cend*bs) { 898 col -= baij->cstart*bs; 899 ierr = MatSetValues(baij->A,1,&row,1,&col,&val,addv); CHKERRQ(ierr) 900 } else { 901 if (mat->was_assembled) { 902 if (!baij->colmap) { 903 ierr = CreateColmap_MPIBAIJ_Private(mat); CHKERRQ(ierr); 904 } 905 col = (baij->colmap[col/bs]) - 1 + col%bs; 906 if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) { 907 ierr = DisAssemble_MPIBAIJ(mat); CHKERRQ(ierr); 908 col = (int) PetscReal(values[3*i+1]); 909 } 910 } 911 ierr = MatSetValues(baij->B,1,&row,1,&col,&val,addv); CHKERRQ(ierr) 912 } 913 } 914 count--; 915 } 916 if (baij->recv_waits) PetscFree(baij->recv_waits); 917 if (baij->rvalues) PetscFree(baij->rvalues); 918 919 /* wait on sends */ 920 if (baij->nsends) { 921 send_status = (MPI_Status *) PetscMalloc(baij->nsends*sizeof(MPI_Status));CHKPTRQ(send_status); 922 ierr = MPI_Waitall(baij->nsends,baij->send_waits,send_status);CHKERRQ(ierr); 923 PetscFree(send_status); 924 } 925 if (baij->send_waits) PetscFree(baij->send_waits); 926 if (baij->svalues) PetscFree(baij->svalues); 927 928 ierr = MatAssemblyBegin(baij->A,mode); CHKERRQ(ierr); 929 ierr = MatAssemblyEnd(baij->A,mode); CHKERRQ(ierr); 930 931 /* determine if any processor has disassembled, if so we must 932 also disassemble ourselfs, in order that we may reassemble. */ 933 /* 934 if nonzero structure of submatrix B cannot change then we know that 935 no processor disassembled thus we can skip this stuff 936 */ 937 if (!((Mat_SeqBAIJ*) baij->B->data)->nonew) { 938 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,mat->comm);CHKERRQ(ierr); 939 if (mat->was_assembled && !other_disassembled) { 940 ierr = DisAssemble_MPIBAIJ(mat); CHKERRQ(ierr); 941 } 942 } 943 944 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 945 ierr = MatSetUpMultiply_MPIBAIJ(mat); CHKERRQ(ierr); 946 } 947 ierr = MatAssemblyBegin(baij->B,mode); CHKERRQ(ierr); 948 ierr = MatAssemblyEnd(baij->B,mode); CHKERRQ(ierr); 949 950 #if defined(USE_PETSC_BOPT_g) 951 if (baij->ht && mode== MAT_FINAL_ASSEMBLY) { 952 PLogInfo(0,"MatAssemblyEnd_MPIBAIJ:Average Hash Table Search in MatSetValues = %5.2f\n", 953 ((double)baij->ht_total_ct)/baij->ht_insert_ct); 954 baij->ht_total_ct = 0; 955 baij->ht_insert_ct = 0; 956 } 957 #endif 958 if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) { 959 ierr = MatCreateHashTable_MPIBAIJ_Private(mat,baij->ht_fact); CHKERRQ(ierr); 960 mat->ops->setvalues = MatSetValues_MPIBAIJ_HT; 961 mat->ops->setvaluesblocked = MatSetValuesBlocked_MPIBAIJ_HT; 962 } 963 964 if (baij->rowvalues) {PetscFree(baij->rowvalues); baij->rowvalues = 0;} 965 PetscFunctionReturn(0); 966 } 967 968 #undef __FUNC__ 969 #define __FUNC__ "MatView_MPIBAIJ_Binary" 970 static int MatView_MPIBAIJ_Binary(Mat mat,Viewer viewer) 971 { 972 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 973 int ierr; 974 975 PetscFunctionBegin; 976 if (baij->size == 1) { 977 ierr = MatView(baij->A,viewer); CHKERRQ(ierr); 978 } else SETERRQ(PETSC_ERR_SUP,0,"Only uniprocessor output supported"); 979 PetscFunctionReturn(0); 980 } 981 982 #undef __FUNC__ 983 #define __FUNC__ "MatView_MPIBAIJ_ASCIIorDraworMatlab" 984 static int MatView_MPIBAIJ_ASCIIorDraworMatlab(Mat mat,Viewer viewer) 985 { 986 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 987 int ierr, format,rank,bs = baij->bs; 988 FILE *fd; 989 ViewerType vtype; 990 991 PetscFunctionBegin; 992 ierr = ViewerGetType(viewer,&vtype); CHKERRQ(ierr); 993 if (vtype == ASCII_FILES_VIEWER || vtype == ASCII_FILE_VIEWER) { 994 ierr = ViewerGetFormat(viewer,&format); 995 if (format == VIEWER_FORMAT_ASCII_INFO_LONG) { 996 MatInfo info; 997 MPI_Comm_rank(mat->comm,&rank); 998 ierr = ViewerASCIIGetPointer(viewer,&fd); CHKERRQ(ierr); 999 ierr = MatGetInfo(mat,MAT_LOCAL,&info); 1000 PetscSequentialPhaseBegin(mat->comm,1); 1001 fprintf(fd,"[%d] Local rows %d nz %d nz alloced %d bs %d mem %d\n", 1002 rank,baij->m,(int)info.nz_used*bs,(int)info.nz_allocated*bs, 1003 baij->bs,(int)info.memory); 1004 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info); 1005 fprintf(fd,"[%d] on-diagonal part: nz %d \n",rank,(int)info.nz_used*bs); 1006 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info); 1007 fprintf(fd,"[%d] off-diagonal part: nz %d \n",rank,(int)info.nz_used*bs); 1008 fflush(fd); 1009 PetscSequentialPhaseEnd(mat->comm,1); 1010 ierr = VecScatterView(baij->Mvctx,viewer); CHKERRQ(ierr); 1011 PetscFunctionReturn(0); 1012 } else if (format == VIEWER_FORMAT_ASCII_INFO) { 1013 PetscPrintf(mat->comm," block size is %d\n",bs); 1014 PetscFunctionReturn(0); 1015 } 1016 } 1017 1018 if (vtype == DRAW_VIEWER) { 1019 Draw draw; 1020 PetscTruth isnull; 1021 ierr = ViewerDrawGetDraw(viewer,&draw); CHKERRQ(ierr); 1022 ierr = DrawIsNull(draw,&isnull); CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 1023 } 1024 1025 if (vtype == ASCII_FILE_VIEWER) { 1026 ierr = ViewerASCIIGetPointer(viewer,&fd); CHKERRQ(ierr); 1027 PetscSequentialPhaseBegin(mat->comm,1); 1028 fprintf(fd,"[%d] rows %d starts %d ends %d cols %d starts %d ends %d\n", 1029 baij->rank,baij->m,baij->rstart*bs,baij->rend*bs,baij->n, 1030 baij->cstart*bs,baij->cend*bs); 1031 ierr = MatView(baij->A,viewer); CHKERRQ(ierr); 1032 ierr = MatView(baij->B,viewer); CHKERRQ(ierr); 1033 fflush(fd); 1034 PetscSequentialPhaseEnd(mat->comm,1); 1035 } else { 1036 int size = baij->size; 1037 rank = baij->rank; 1038 if (size == 1) { 1039 ierr = MatView(baij->A,viewer); CHKERRQ(ierr); 1040 } else { 1041 /* assemble the entire matrix onto first processor. */ 1042 Mat A; 1043 Mat_SeqBAIJ *Aloc; 1044 int M = baij->M, N = baij->N,*ai,*aj,col,i,j,k,*rvals; 1045 int mbs=baij->mbs; 1046 Scalar *a; 1047 1048 if (!rank) { 1049 ierr = MatCreateMPIBAIJ(mat->comm,baij->bs,M,N,M,N,0,PETSC_NULL,0,PETSC_NULL,&A);CHKERRQ(ierr); 1050 } else { 1051 ierr = MatCreateMPIBAIJ(mat->comm,baij->bs,0,0,M,N,0,PETSC_NULL,0,PETSC_NULL,&A);CHKERRQ(ierr); 1052 } 1053 PLogObjectParent(mat,A); 1054 1055 /* copy over the A part */ 1056 Aloc = (Mat_SeqBAIJ*) baij->A->data; 1057 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1058 rvals = (int *) PetscMalloc(bs*sizeof(int)); CHKPTRQ(rvals); 1059 1060 for ( i=0; i<mbs; i++ ) { 1061 rvals[0] = bs*(baij->rstart + i); 1062 for ( j=1; j<bs; j++ ) { rvals[j] = rvals[j-1] + 1; } 1063 for ( j=ai[i]; j<ai[i+1]; j++ ) { 1064 col = (baij->cstart+aj[j])*bs; 1065 for (k=0; k<bs; k++ ) { 1066 ierr = MatSetValues(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1067 col++; a += bs; 1068 } 1069 } 1070 } 1071 /* copy over the B part */ 1072 Aloc = (Mat_SeqBAIJ*) baij->B->data; 1073 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1074 for ( i=0; i<mbs; i++ ) { 1075 rvals[0] = bs*(baij->rstart + i); 1076 for ( j=1; j<bs; j++ ) { rvals[j] = rvals[j-1] + 1; } 1077 for ( j=ai[i]; j<ai[i+1]; j++ ) { 1078 col = baij->garray[aj[j]]*bs; 1079 for (k=0; k<bs; k++ ) { 1080 ierr = MatSetValues(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 1081 col++; a += bs; 1082 } 1083 } 1084 } 1085 PetscFree(rvals); 1086 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1087 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1088 /* 1089 Everyone has to call to draw the matrix since the graphics waits are 1090 synchronized across all processors that share the Draw object 1091 */ 1092 if (!rank || vtype == DRAW_VIEWER) { 1093 ierr = MatView(((Mat_MPIBAIJ*)(A->data))->A,viewer); CHKERRQ(ierr); 1094 } 1095 ierr = MatDestroy(A); CHKERRQ(ierr); 1096 } 1097 } 1098 PetscFunctionReturn(0); 1099 } 1100 1101 1102 1103 #undef __FUNC__ 1104 #define __FUNC__ "MatView_MPIBAIJ" 1105 int MatView_MPIBAIJ(Mat mat,Viewer viewer) 1106 { 1107 int ierr; 1108 ViewerType vtype; 1109 1110 PetscFunctionBegin; 1111 ierr = ViewerGetType(viewer,&vtype); CHKERRQ(ierr); 1112 if (vtype == ASCII_FILE_VIEWER || vtype == ASCII_FILES_VIEWER || 1113 vtype == DRAW_VIEWER || vtype == MATLAB_VIEWER) { 1114 ierr = MatView_MPIBAIJ_ASCIIorDraworMatlab(mat,viewer); CHKERRQ(ierr); 1115 } else if (vtype == BINARY_FILE_VIEWER) { 1116 ierr = MatView_MPIBAIJ_Binary(mat,viewer);CHKERRQ(ierr); 1117 } else { 1118 SETERRQ(1,1,"Viewer type not supported by PETSc object"); 1119 } 1120 PetscFunctionReturn(0); 1121 } 1122 1123 #undef __FUNC__ 1124 #define __FUNC__ "MatDestroy_MPIBAIJ" 1125 int MatDestroy_MPIBAIJ(Mat mat) 1126 { 1127 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 1128 int ierr; 1129 1130 PetscFunctionBegin; 1131 if (--mat->refct > 0) PetscFunctionReturn(0); 1132 1133 if (mat->mapping) { 1134 ierr = ISLocalToGlobalMappingDestroy(mat->mapping); CHKERRQ(ierr); 1135 } 1136 if (mat->bmapping) { 1137 ierr = ISLocalToGlobalMappingDestroy(mat->bmapping); CHKERRQ(ierr); 1138 } 1139 if (mat->rmap) { 1140 ierr = MapDestroy(mat->rmap);CHKERRQ(ierr); 1141 } 1142 if (mat->cmap) { 1143 ierr = MapDestroy(mat->cmap);CHKERRQ(ierr); 1144 } 1145 #if defined(USE_PETSC_LOG) 1146 PLogObjectState((PetscObject)mat,"Rows=%d, Cols=%d",baij->M,baij->N); 1147 #endif 1148 1149 ierr = StashDestroy_Private(&baij->stash); CHKERRQ(ierr); 1150 PetscFree(baij->rowners); 1151 ierr = MatDestroy(baij->A); CHKERRQ(ierr); 1152 ierr = MatDestroy(baij->B); CHKERRQ(ierr); 1153 if (baij->colmap) PetscFree(baij->colmap); 1154 if (baij->garray) PetscFree(baij->garray); 1155 if (baij->lvec) VecDestroy(baij->lvec); 1156 if (baij->Mvctx) VecScatterDestroy(baij->Mvctx); 1157 if (baij->rowvalues) PetscFree(baij->rowvalues); 1158 if (baij->barray) PetscFree(baij->barray); 1159 if (baij->hd) PetscFree(baij->hd); 1160 PetscFree(baij); 1161 PLogObjectDestroy(mat); 1162 PetscHeaderDestroy(mat); 1163 PetscFunctionReturn(0); 1164 } 1165 1166 #undef __FUNC__ 1167 #define __FUNC__ "MatMult_MPIBAIJ" 1168 int MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy) 1169 { 1170 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data; 1171 int ierr, nt; 1172 1173 PetscFunctionBegin; 1174 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 1175 if (nt != a->n) { 1176 SETERRQ(PETSC_ERR_ARG_SIZ,0,"Incompatible partition of A and xx"); 1177 } 1178 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 1179 if (nt != a->m) { 1180 SETERRQ(PETSC_ERR_ARG_SIZ,0,"Incompatible parition of A and yy"); 1181 } 1182 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1183 ierr = (*a->A->ops->mult)(a->A,xx,yy); CHKERRQ(ierr); 1184 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1185 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy); CHKERRQ(ierr); 1186 ierr = VecScatterPostRecvs(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1187 PetscFunctionReturn(0); 1188 } 1189 1190 #undef __FUNC__ 1191 #define __FUNC__ "MatMultAdd_MPIBAIJ" 1192 int MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1193 { 1194 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data; 1195 int ierr; 1196 1197 PetscFunctionBegin; 1198 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1199 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz); CHKERRQ(ierr); 1200 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 1201 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz); CHKERRQ(ierr); 1202 PetscFunctionReturn(0); 1203 } 1204 1205 #undef __FUNC__ 1206 #define __FUNC__ "MatMultTrans_MPIBAIJ" 1207 int MatMultTrans_MPIBAIJ(Mat A,Vec xx,Vec yy) 1208 { 1209 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data; 1210 int ierr; 1211 1212 PetscFunctionBegin; 1213 /* do nondiagonal part */ 1214 ierr = (*a->B->ops->multtrans)(a->B,xx,a->lvec); CHKERRQ(ierr); 1215 /* send it on its way */ 1216 ierr = VecScatterBegin(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1217 /* do local part */ 1218 ierr = (*a->A->ops->multtrans)(a->A,xx,yy); CHKERRQ(ierr); 1219 /* receive remote parts: note this assumes the values are not actually */ 1220 /* inserted in yy until the next line, which is true for my implementation*/ 1221 /* but is not perhaps always true. */ 1222 ierr = VecScatterEnd(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 1223 PetscFunctionReturn(0); 1224 } 1225 1226 #undef __FUNC__ 1227 #define __FUNC__ "MatMultTransAdd_MPIBAIJ" 1228 int MatMultTransAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1229 { 1230 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data; 1231 int ierr; 1232 1233 PetscFunctionBegin; 1234 /* do nondiagonal part */ 1235 ierr = (*a->B->ops->multtrans)(a->B,xx,a->lvec); CHKERRQ(ierr); 1236 /* send it on its way */ 1237 ierr = VecScatterBegin(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx); CHKERRQ(ierr); 1238 /* do local part */ 1239 ierr = (*a->A->ops->multtransadd)(a->A,xx,yy,zz); CHKERRQ(ierr); 1240 /* receive remote parts: note this assumes the values are not actually */ 1241 /* inserted in yy until the next line, which is true for my implementation*/ 1242 /* but is not perhaps always true. */ 1243 ierr = VecScatterEnd(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx); CHKERRQ(ierr); 1244 PetscFunctionReturn(0); 1245 } 1246 1247 /* 1248 This only works correctly for square matrices where the subblock A->A is the 1249 diagonal block 1250 */ 1251 #undef __FUNC__ 1252 #define __FUNC__ "MatGetDiagonal_MPIBAIJ" 1253 int MatGetDiagonal_MPIBAIJ(Mat A,Vec v) 1254 { 1255 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data; 1256 int ierr; 1257 1258 PetscFunctionBegin; 1259 if (a->M != a->N) SETERRQ(PETSC_ERR_SUP,0,"Supports only square matrix where A->A is diag block"); 1260 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 1261 PetscFunctionReturn(0); 1262 } 1263 1264 #undef __FUNC__ 1265 #define __FUNC__ "MatScale_MPIBAIJ" 1266 int MatScale_MPIBAIJ(Scalar *aa,Mat A) 1267 { 1268 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data; 1269 int ierr; 1270 1271 PetscFunctionBegin; 1272 ierr = MatScale(aa,a->A); CHKERRQ(ierr); 1273 ierr = MatScale(aa,a->B); CHKERRQ(ierr); 1274 PetscFunctionReturn(0); 1275 } 1276 1277 #undef __FUNC__ 1278 #define __FUNC__ "MatGetSize_MPIBAIJ" 1279 int MatGetSize_MPIBAIJ(Mat matin,int *m,int *n) 1280 { 1281 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ *) matin->data; 1282 1283 PetscFunctionBegin; 1284 if (m) *m = mat->M; 1285 if (n) *n = mat->N; 1286 PetscFunctionReturn(0); 1287 } 1288 1289 #undef __FUNC__ 1290 #define __FUNC__ "MatGetLocalSize_MPIBAIJ" 1291 int MatGetLocalSize_MPIBAIJ(Mat matin,int *m,int *n) 1292 { 1293 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ *) matin->data; 1294 1295 PetscFunctionBegin; 1296 *m = mat->m; *n = mat->n; 1297 PetscFunctionReturn(0); 1298 } 1299 1300 #undef __FUNC__ 1301 #define __FUNC__ "MatGetOwnershipRange_MPIBAIJ" 1302 int MatGetOwnershipRange_MPIBAIJ(Mat matin,int *m,int *n) 1303 { 1304 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ *) matin->data; 1305 1306 PetscFunctionBegin; 1307 *m = mat->rstart*mat->bs; *n = mat->rend*mat->bs; 1308 PetscFunctionReturn(0); 1309 } 1310 1311 extern int MatGetRow_SeqBAIJ(Mat,int,int*,int**,Scalar**); 1312 extern int MatRestoreRow_SeqBAIJ(Mat,int,int*,int**,Scalar**); 1313 1314 #undef __FUNC__ 1315 #define __FUNC__ "MatGetRow_MPIBAIJ" 1316 int MatGetRow_MPIBAIJ(Mat matin,int row,int *nz,int **idx,Scalar **v) 1317 { 1318 Mat_MPIBAIJ *mat = (Mat_MPIBAIJ *) matin->data; 1319 Scalar *vworkA, *vworkB, **pvA, **pvB,*v_p; 1320 int bs = mat->bs, bs2 = mat->bs2, i, ierr, *cworkA, *cworkB, **pcA, **pcB; 1321 int nztot, nzA, nzB, lrow, brstart = mat->rstart*bs, brend = mat->rend*bs; 1322 int *cmap, *idx_p,cstart = mat->cstart; 1323 1324 PetscFunctionBegin; 1325 if (mat->getrowactive == PETSC_TRUE) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Already active"); 1326 mat->getrowactive = PETSC_TRUE; 1327 1328 if (!mat->rowvalues && (idx || v)) { 1329 /* 1330 allocate enough space to hold information from the longest row. 1331 */ 1332 Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ *) mat->A->data,*Ba = (Mat_SeqBAIJ *) mat->B->data; 1333 int max = 1,mbs = mat->mbs,tmp; 1334 for ( i=0; i<mbs; i++ ) { 1335 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; 1336 if (max < tmp) { max = tmp; } 1337 } 1338 mat->rowvalues = (Scalar *) PetscMalloc( max*bs2*(sizeof(int)+sizeof(Scalar))); 1339 CHKPTRQ(mat->rowvalues); 1340 mat->rowindices = (int *) (mat->rowvalues + max*bs2); 1341 } 1342 1343 if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,0,"Only local rows") 1344 lrow = row - brstart; 1345 1346 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1347 if (!v) {pvA = 0; pvB = 0;} 1348 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1349 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA); CHKERRQ(ierr); 1350 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB); CHKERRQ(ierr); 1351 nztot = nzA + nzB; 1352 1353 cmap = mat->garray; 1354 if (v || idx) { 1355 if (nztot) { 1356 /* Sort by increasing column numbers, assuming A and B already sorted */ 1357 int imark = -1; 1358 if (v) { 1359 *v = v_p = mat->rowvalues; 1360 for ( i=0; i<nzB; i++ ) { 1361 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1362 else break; 1363 } 1364 imark = i; 1365 for ( i=0; i<nzA; i++ ) v_p[imark+i] = vworkA[i]; 1366 for ( i=imark; i<nzB; i++ ) v_p[nzA+i] = vworkB[i]; 1367 } 1368 if (idx) { 1369 *idx = idx_p = mat->rowindices; 1370 if (imark > -1) { 1371 for ( i=0; i<imark; i++ ) { 1372 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1373 } 1374 } else { 1375 for ( i=0; i<nzB; i++ ) { 1376 if (cmap[cworkB[i]/bs] < cstart) 1377 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1378 else break; 1379 } 1380 imark = i; 1381 } 1382 for ( i=0; i<nzA; i++ ) idx_p[imark+i] = cstart*bs + cworkA[i]; 1383 for ( i=imark; i<nzB; i++ ) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1384 } 1385 } else { 1386 if (idx) *idx = 0; 1387 if (v) *v = 0; 1388 } 1389 } 1390 *nz = nztot; 1391 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA); CHKERRQ(ierr); 1392 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB); CHKERRQ(ierr); 1393 PetscFunctionReturn(0); 1394 } 1395 1396 #undef __FUNC__ 1397 #define __FUNC__ "MatRestoreRow_MPIBAIJ" 1398 int MatRestoreRow_MPIBAIJ(Mat mat,int row,int *nz,int **idx,Scalar **v) 1399 { 1400 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 1401 1402 PetscFunctionBegin; 1403 if (baij->getrowactive == PETSC_FALSE) { 1404 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"MatGetRow not called"); 1405 } 1406 baij->getrowactive = PETSC_FALSE; 1407 PetscFunctionReturn(0); 1408 } 1409 1410 #undef __FUNC__ 1411 #define __FUNC__ "MatGetBlockSize_MPIBAIJ" 1412 int MatGetBlockSize_MPIBAIJ(Mat mat,int *bs) 1413 { 1414 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) mat->data; 1415 1416 PetscFunctionBegin; 1417 *bs = baij->bs; 1418 PetscFunctionReturn(0); 1419 } 1420 1421 #undef __FUNC__ 1422 #define __FUNC__ "MatZeroEntries_MPIBAIJ" 1423 int MatZeroEntries_MPIBAIJ(Mat A) 1424 { 1425 Mat_MPIBAIJ *l = (Mat_MPIBAIJ *) A->data; 1426 int ierr; 1427 1428 PetscFunctionBegin; 1429 ierr = MatZeroEntries(l->A); CHKERRQ(ierr); 1430 ierr = MatZeroEntries(l->B); CHKERRQ(ierr); 1431 PetscFunctionReturn(0); 1432 } 1433 1434 #undef __FUNC__ 1435 #define __FUNC__ "MatGetInfo_MPIBAIJ" 1436 int MatGetInfo_MPIBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1437 { 1438 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) matin->data; 1439 Mat A = a->A, B = a->B; 1440 int ierr; 1441 double isend[5], irecv[5]; 1442 1443 PetscFunctionBegin; 1444 info->block_size = (double)a->bs; 1445 ierr = MatGetInfo(A,MAT_LOCAL,info); CHKERRQ(ierr); 1446 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1447 isend[3] = info->memory; isend[4] = info->mallocs; 1448 ierr = MatGetInfo(B,MAT_LOCAL,info); CHKERRQ(ierr); 1449 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1450 isend[3] += info->memory; isend[4] += info->mallocs; 1451 if (flag == MAT_LOCAL) { 1452 info->nz_used = isend[0]; 1453 info->nz_allocated = isend[1]; 1454 info->nz_unneeded = isend[2]; 1455 info->memory = isend[3]; 1456 info->mallocs = isend[4]; 1457 } else if (flag == MAT_GLOBAL_MAX) { 1458 ierr = MPI_Allreduce(isend,irecv,5,MPI_DOUBLE,MPI_MAX,matin->comm);CHKERRQ(ierr); 1459 info->nz_used = irecv[0]; 1460 info->nz_allocated = irecv[1]; 1461 info->nz_unneeded = irecv[2]; 1462 info->memory = irecv[3]; 1463 info->mallocs = irecv[4]; 1464 } else if (flag == MAT_GLOBAL_SUM) { 1465 ierr = MPI_Allreduce(isend,irecv,5,MPI_DOUBLE,MPI_SUM,matin->comm);CHKERRQ(ierr); 1466 info->nz_used = irecv[0]; 1467 info->nz_allocated = irecv[1]; 1468 info->nz_unneeded = irecv[2]; 1469 info->memory = irecv[3]; 1470 info->mallocs = irecv[4]; 1471 } 1472 info->rows_global = (double)a->M; 1473 info->columns_global = (double)a->N; 1474 info->rows_local = (double)a->m; 1475 info->columns_local = (double)a->N; 1476 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1477 info->fill_ratio_needed = 0; 1478 info->factor_mallocs = 0; 1479 PetscFunctionReturn(0); 1480 } 1481 1482 #undef __FUNC__ 1483 #define __FUNC__ "MatSetOption_MPIBAIJ" 1484 int MatSetOption_MPIBAIJ(Mat A,MatOption op) 1485 { 1486 Mat_MPIBAIJ *a = (Mat_MPIBAIJ *) A->data; 1487 1488 PetscFunctionBegin; 1489 if (op == MAT_NO_NEW_NONZERO_LOCATIONS || 1490 op == MAT_YES_NEW_NONZERO_LOCATIONS || 1491 op == MAT_COLUMNS_UNSORTED || 1492 op == MAT_COLUMNS_SORTED || 1493 op == MAT_NEW_NONZERO_ALLOCATION_ERROR || 1494 op == MAT_NEW_NONZERO_LOCATION_ERROR) { 1495 MatSetOption(a->A,op); 1496 MatSetOption(a->B,op); 1497 } else if (op == MAT_ROW_ORIENTED) { 1498 a->roworiented = 1; 1499 MatSetOption(a->A,op); 1500 MatSetOption(a->B,op); 1501 } else if (op == MAT_ROWS_SORTED || 1502 op == MAT_ROWS_UNSORTED || 1503 op == MAT_SYMMETRIC || 1504 op == MAT_STRUCTURALLY_SYMMETRIC || 1505 op == MAT_YES_NEW_DIAGONALS || 1506 op == MAT_USE_HASH_TABLE) 1507 PLogInfo(A,"Info:MatSetOption_MPIBAIJ:Option ignored\n"); 1508 else if (op == MAT_COLUMN_ORIENTED) { 1509 a->roworiented = 0; 1510 MatSetOption(a->A,op); 1511 MatSetOption(a->B,op); 1512 } else if (op == MAT_IGNORE_OFF_PROC_ENTRIES) { 1513 a->donotstash = 1; 1514 } else if (op == MAT_NO_NEW_DIAGONALS) { 1515 SETERRQ(PETSC_ERR_SUP,0,"MAT_NO_NEW_DIAGONALS"); 1516 } else if (op == MAT_USE_HASH_TABLE) { 1517 a->ht_flag = 1; 1518 } else { 1519 SETERRQ(PETSC_ERR_SUP,0,"unknown option"); 1520 } 1521 PetscFunctionReturn(0); 1522 } 1523 1524 #undef __FUNC__ 1525 #define __FUNC__ "MatTranspose_MPIBAIJ(" 1526 int MatTranspose_MPIBAIJ(Mat A,Mat *matout) 1527 { 1528 Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *) A->data; 1529 Mat_SeqBAIJ *Aloc; 1530 Mat B; 1531 int ierr,M=baij->M,N=baij->N,*ai,*aj,i,*rvals,j,k,col; 1532 int bs=baij->bs,mbs=baij->mbs; 1533 Scalar *a; 1534 1535 PetscFunctionBegin; 1536 if (matout == PETSC_NULL && M != N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Square matrix only for in-place"); 1537 ierr = MatCreateMPIBAIJ(A->comm,baij->bs,PETSC_DECIDE,PETSC_DECIDE,N,M,0,PETSC_NULL,0,PETSC_NULL,&B); 1538 CHKERRQ(ierr); 1539 1540 /* copy over the A part */ 1541 Aloc = (Mat_SeqBAIJ*) baij->A->data; 1542 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1543 rvals = (int *) PetscMalloc(bs*sizeof(int)); CHKPTRQ(rvals); 1544 1545 for ( i=0; i<mbs; i++ ) { 1546 rvals[0] = bs*(baij->rstart + i); 1547 for ( j=1; j<bs; j++ ) { rvals[j] = rvals[j-1] + 1; } 1548 for ( j=ai[i]; j<ai[i+1]; j++ ) { 1549 col = (baij->cstart+aj[j])*bs; 1550 for (k=0; k<bs; k++ ) { 1551 ierr = MatSetValues(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1552 col++; a += bs; 1553 } 1554 } 1555 } 1556 /* copy over the B part */ 1557 Aloc = (Mat_SeqBAIJ*) baij->B->data; 1558 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 1559 for ( i=0; i<mbs; i++ ) { 1560 rvals[0] = bs*(baij->rstart + i); 1561 for ( j=1; j<bs; j++ ) { rvals[j] = rvals[j-1] + 1; } 1562 for ( j=ai[i]; j<ai[i+1]; j++ ) { 1563 col = baij->garray[aj[j]]*bs; 1564 for (k=0; k<bs; k++ ) { 1565 ierr = MatSetValues(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr); 1566 col++; a += bs; 1567 } 1568 } 1569 } 1570 PetscFree(rvals); 1571 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1572 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1573 1574 if (matout != PETSC_NULL) { 1575 *matout = B; 1576 } else { 1577 PetscOps *Abops; 1578 MatOps Aops; 1579 1580 /* This isn't really an in-place transpose .... but free data structures from baij */ 1581 PetscFree(baij->rowners); 1582 ierr = MatDestroy(baij->A); CHKERRQ(ierr); 1583 ierr = MatDestroy(baij->B); CHKERRQ(ierr); 1584 if (baij->colmap) PetscFree(baij->colmap); 1585 if (baij->garray) PetscFree(baij->garray); 1586 if (baij->lvec) VecDestroy(baij->lvec); 1587 if (baij->Mvctx) VecScatterDestroy(baij->Mvctx); 1588 PetscFree(baij); 1589 1590 /* 1591 This is horrible, horrible code. We need to keep the 1592 A pointers for the bops and ops but copy everything 1593 else from C. 1594 */ 1595 Abops = A->bops; 1596 Aops = A->ops; 1597 PetscMemcpy(A,B,sizeof(struct _p_Mat)); 1598 A->bops = Abops; 1599 A->ops = Aops; 1600 1601 PetscHeaderDestroy(B); 1602 } 1603 PetscFunctionReturn(0); 1604 } 1605 1606 #undef __FUNC__ 1607 #define __FUNC__ "MatDiagonalScale_MPIBAIJ" 1608 int MatDiagonalScale_MPIBAIJ(Mat A,Vec ll,Vec rr) 1609 { 1610 Mat a = ((Mat_MPIBAIJ *) A->data)->A; 1611 Mat b = ((Mat_MPIBAIJ *) A->data)->B; 1612 int ierr,s1,s2,s3; 1613 1614 PetscFunctionBegin; 1615 if (ll) { 1616 ierr = VecGetLocalSize(ll,&s1); CHKERRQ(ierr); 1617 ierr = MatGetLocalSize(A,&s2,&s3); CHKERRQ(ierr); 1618 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,0,"non-conforming local sizes"); 1619 ierr = MatDiagonalScale(a,ll,0); CHKERRQ(ierr); 1620 ierr = MatDiagonalScale(b,ll,0); CHKERRQ(ierr); 1621 } 1622 if (rr) SETERRQ(PETSC_ERR_SUP,0,"not supported for right vector"); 1623 PetscFunctionReturn(0); 1624 } 1625 1626 #undef __FUNC__ 1627 #define __FUNC__ "MatZeroRows_MPIBAIJ" 1628 int MatZeroRows_MPIBAIJ(Mat A,IS is,Scalar *diag) 1629 { 1630 Mat_MPIBAIJ *l = (Mat_MPIBAIJ *) A->data; 1631 int i,ierr,N, *rows,*owners = l->rowners,size = l->size; 1632 int *procs,*nprocs,j,found,idx,nsends,*work,row; 1633 int nmax,*svalues,*starts,*owner,nrecvs,rank = l->rank; 1634 int *rvalues,tag = A->tag,count,base,slen,n,*source; 1635 int *lens,imdex,*lrows,*values,bs=l->bs,rstart_bs=l->rstart_bs; 1636 MPI_Comm comm = A->comm; 1637 MPI_Request *send_waits,*recv_waits; 1638 MPI_Status recv_status,*send_status; 1639 IS istmp; 1640 PetscTruth localdiag; 1641 1642 PetscFunctionBegin; 1643 ierr = ISGetSize(is,&N); CHKERRQ(ierr); 1644 ierr = ISGetIndices(is,&rows); CHKERRQ(ierr); 1645 1646 /* first count number of contributors to each processor */ 1647 nprocs = (int *) PetscMalloc( 2*size*sizeof(int) ); CHKPTRQ(nprocs); 1648 PetscMemzero(nprocs,2*size*sizeof(int)); procs = nprocs + size; 1649 owner = (int *) PetscMalloc((N+1)*sizeof(int)); CHKPTRQ(owner); /* see note*/ 1650 for ( i=0; i<N; i++ ) { 1651 idx = rows[i]; 1652 found = 0; 1653 for ( j=0; j<size; j++ ) { 1654 if (idx >= owners[j]*bs && idx < owners[j+1]*bs) { 1655 nprocs[j]++; procs[j] = 1; owner[i] = j; found = 1; break; 1656 } 1657 } 1658 if (!found) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Index out of range"); 1659 } 1660 nsends = 0; for ( i=0; i<size; i++ ) { nsends += procs[i];} 1661 1662 /* inform other processors of number of messages and max length*/ 1663 work = (int *) PetscMalloc( size*sizeof(int) ); CHKPTRQ(work); 1664 ierr = MPI_Allreduce( procs, work,size,MPI_INT,MPI_SUM,comm);CHKERRQ(ierr); 1665 nrecvs = work[rank]; 1666 ierr = MPI_Allreduce( nprocs, work,size,MPI_INT,MPI_MAX,comm);CHKERRQ(ierr); 1667 nmax = work[rank]; 1668 PetscFree(work); 1669 1670 /* post receives: */ 1671 rvalues = (int *) PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(int)); CHKPTRQ(rvalues); 1672 recv_waits = (MPI_Request *) PetscMalloc((nrecvs+1)*sizeof(MPI_Request));CHKPTRQ(recv_waits); 1673 for ( i=0; i<nrecvs; i++ ) { 1674 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPI_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 1675 } 1676 1677 /* do sends: 1678 1) starts[i] gives the starting index in svalues for stuff going to 1679 the ith processor 1680 */ 1681 svalues = (int *) PetscMalloc( (N+1)*sizeof(int) ); CHKPTRQ(svalues); 1682 send_waits = (MPI_Request *) PetscMalloc( (nsends+1)*sizeof(MPI_Request));CHKPTRQ(send_waits); 1683 starts = (int *) PetscMalloc( (size+1)*sizeof(int) ); CHKPTRQ(starts); 1684 starts[0] = 0; 1685 for ( i=1; i<size; i++ ) { starts[i] = starts[i-1] + nprocs[i-1];} 1686 for ( i=0; i<N; i++ ) { 1687 svalues[starts[owner[i]]++] = rows[i]; 1688 } 1689 ISRestoreIndices(is,&rows); 1690 1691 starts[0] = 0; 1692 for ( i=1; i<size+1; i++ ) { starts[i] = starts[i-1] + nprocs[i-1];} 1693 count = 0; 1694 for ( i=0; i<size; i++ ) { 1695 if (procs[i]) { 1696 ierr = MPI_Isend(svalues+starts[i],nprocs[i],MPI_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 1697 } 1698 } 1699 PetscFree(starts); 1700 1701 base = owners[rank]*bs; 1702 1703 /* wait on receives */ 1704 lens = (int *) PetscMalloc( 2*(nrecvs+1)*sizeof(int) ); CHKPTRQ(lens); 1705 source = lens + nrecvs; 1706 count = nrecvs; slen = 0; 1707 while (count) { 1708 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 1709 /* unpack receives into our local space */ 1710 ierr = MPI_Get_count(&recv_status,MPI_INT,&n);CHKERRQ(ierr); 1711 source[imdex] = recv_status.MPI_SOURCE; 1712 lens[imdex] = n; 1713 slen += n; 1714 count--; 1715 } 1716 PetscFree(recv_waits); 1717 1718 /* move the data into the send scatter */ 1719 lrows = (int *) PetscMalloc( (slen+1)*sizeof(int) ); CHKPTRQ(lrows); 1720 count = 0; 1721 for ( i=0; i<nrecvs; i++ ) { 1722 values = rvalues + i*nmax; 1723 for ( j=0; j<lens[i]; j++ ) { 1724 lrows[count++] = values[j] - base; 1725 } 1726 } 1727 PetscFree(rvalues); PetscFree(lens); 1728 PetscFree(owner); PetscFree(nprocs); 1729 1730 /* actually zap the local rows */ 1731 ierr = ISCreateGeneral(PETSC_COMM_SELF,slen,lrows,&istmp);CHKERRQ(ierr); 1732 PLogObjectParent(A,istmp); 1733 1734 /* 1735 Zero the required rows. If the "diagonal block" of the matrix 1736 is square and the user wishes to set the diagonal we use seperate 1737 code so that MatSetValues() is not called for each diagonal allocating 1738 new memory, thus calling lots of mallocs and slowing things down. 1739 1740 Contributed by: Mathew Knepley 1741 */ 1742 localdiag = PETSC_FALSE; 1743 if (diag && (l->A->M == l->A->N)) { 1744 localdiag = PETSC_TRUE; 1745 ierr = MatZeroRows(l->A,istmp,diag); CHKERRQ(ierr); 1746 } else { 1747 ierr = MatZeroRows(l->A,istmp,0); CHKERRQ(ierr); 1748 } 1749 ierr = MatZeroRows(l->B,istmp,0); CHKERRQ(ierr); 1750 ierr = ISDestroy(istmp); CHKERRQ(ierr); 1751 1752 if (diag && (localdiag == PETSC_FALSE)) { 1753 for ( i = 0; i < slen; i++ ) { 1754 row = lrows[i] + rstart_bs; 1755 ierr = MatSetValues(A,1,&row,1,&row,diag,INSERT_VALUES); CHKERRQ(ierr); 1756 } 1757 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1758 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1759 } 1760 PetscFree(lrows); 1761 1762 /* wait on sends */ 1763 if (nsends) { 1764 send_status = (MPI_Status *) PetscMalloc(nsends*sizeof(MPI_Status));CHKPTRQ(send_status); 1765 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 1766 PetscFree(send_status); 1767 } 1768 PetscFree(send_waits); PetscFree(svalues); 1769 1770 PetscFunctionReturn(0); 1771 } 1772 1773 extern int MatPrintHelp_SeqBAIJ(Mat); 1774 #undef __FUNC__ 1775 #define __FUNC__ "MatPrintHelp_MPIBAIJ" 1776 int MatPrintHelp_MPIBAIJ(Mat A) 1777 { 1778 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*) A->data; 1779 MPI_Comm comm = A->comm; 1780 static int called = 0; 1781 int ierr; 1782 1783 PetscFunctionBegin; 1784 if (!a->rank) { 1785 ierr = MatPrintHelp_SeqBAIJ(a->A);CHKERRQ(ierr); 1786 } 1787 if (called) {PetscFunctionReturn(0);} else called = 1; 1788 (*PetscHelpPrintf)(comm," Options for MATMPIBAIJ matrix format (the defaults):\n"); 1789 (*PetscHelpPrintf)(comm," -mat_use_hash_table <factor>: Use hashtable for efficient matrix assembly\n"); 1790 PetscFunctionReturn(0); 1791 } 1792 1793 #undef __FUNC__ 1794 #define __FUNC__ "MatSetUnfactored_MPIBAIJ" 1795 int MatSetUnfactored_MPIBAIJ(Mat A) 1796 { 1797 Mat_MPIBAIJ *a = (Mat_MPIBAIJ*) A->data; 1798 int ierr; 1799 1800 PetscFunctionBegin; 1801 ierr = MatSetUnfactored(a->A); CHKERRQ(ierr); 1802 PetscFunctionReturn(0); 1803 } 1804 1805 static int MatConvertSameType_MPIBAIJ(Mat,Mat *,int); 1806 1807 /* -------------------------------------------------------------------*/ 1808 static struct _MatOps MatOps_Values = { 1809 MatSetValues_MPIBAIJ, 1810 MatGetRow_MPIBAIJ, 1811 MatRestoreRow_MPIBAIJ, 1812 MatMult_MPIBAIJ, 1813 MatMultAdd_MPIBAIJ, 1814 MatMultTrans_MPIBAIJ, 1815 MatMultTransAdd_MPIBAIJ, 1816 0, 1817 0, 1818 0, 1819 0, 1820 0, 1821 0, 1822 0, 1823 MatTranspose_MPIBAIJ, 1824 MatGetInfo_MPIBAIJ, 1825 0, 1826 MatGetDiagonal_MPIBAIJ, 1827 MatDiagonalScale_MPIBAIJ, 1828 MatNorm_MPIBAIJ, 1829 MatAssemblyBegin_MPIBAIJ, 1830 MatAssemblyEnd_MPIBAIJ, 1831 0, 1832 MatSetOption_MPIBAIJ, 1833 MatZeroEntries_MPIBAIJ, 1834 MatZeroRows_MPIBAIJ, 1835 0, 1836 0, 1837 0, 1838 0, 1839 MatGetSize_MPIBAIJ, 1840 MatGetLocalSize_MPIBAIJ, 1841 MatGetOwnershipRange_MPIBAIJ, 1842 0, 1843 0, 1844 0, 1845 0, 1846 MatConvertSameType_MPIBAIJ, 1847 0, 1848 0, 1849 0, 1850 0, 1851 0, 1852 MatGetSubMatrices_MPIBAIJ, 1853 MatIncreaseOverlap_MPIBAIJ, 1854 MatGetValues_MPIBAIJ, 1855 0, 1856 MatPrintHelp_MPIBAIJ, 1857 MatScale_MPIBAIJ, 1858 0, 1859 0, 1860 0, 1861 MatGetBlockSize_MPIBAIJ, 1862 0, 1863 0, 1864 0, 1865 0, 1866 0, 1867 0, 1868 MatSetUnfactored_MPIBAIJ, 1869 0, 1870 MatSetValuesBlocked_MPIBAIJ, 1871 0, 1872 0, 1873 0, 1874 MatGetMaps_Petsc}; 1875 1876 1877 #undef __FUNC__ 1878 #define __FUNC__ "MatCreateMPIBAIJ" 1879 /*@C 1880 MatCreateMPIBAIJ - Creates a sparse parallel matrix in block AIJ format 1881 (block compressed row). For good matrix assembly performance 1882 the user should preallocate the matrix storage by setting the parameters 1883 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1884 performance can be increased by more than a factor of 50. 1885 1886 Collective on MPI_Comm 1887 1888 Input Parameters: 1889 + comm - MPI communicator 1890 . bs - size of blockk 1891 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1892 This value should be the same as the local size used in creating the 1893 y vector for the matrix-vector product y = Ax. 1894 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1895 This value should be the same as the local size used in creating the 1896 x vector for the matrix-vector product y = Ax. 1897 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1898 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1899 . d_nz - number of block nonzeros per block row in diagonal portion of local 1900 submatrix (same for all local rows) 1901 . d_nzz - array containing the number of block nonzeros in the various block rows 1902 of the in diagonal portion of the local (possibly different for each block 1903 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 1904 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1905 submatrix (same for all local rows). 1906 - o_nzz - array containing the number of nonzeros in the various block rows of the 1907 off-diagonal portion of the local submatrix (possibly different for 1908 each block row) or PETSC_NULL. 1909 1910 Output Parameter: 1911 . A - the matrix 1912 1913 Options Database Keys: 1914 . -mat_no_unroll - uses code that does not unroll the loops in the 1915 block calculations (much slower) 1916 . -mat_block_size - size of the blocks to use 1917 1918 Notes: 1919 The user MUST specify either the local or global matrix dimensions 1920 (possibly both). 1921 1922 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1923 than it must be used on all processors that share the object for that argument. 1924 1925 Storage Information: 1926 For a square global matrix we define each processor's diagonal portion 1927 to be its local rows and the corresponding columns (a square submatrix); 1928 each processor's off-diagonal portion encompasses the remainder of the 1929 local matrix (a rectangular submatrix). 1930 1931 The user can specify preallocated storage for the diagonal part of 1932 the local submatrix with either d_nz or d_nnz (not both). Set 1933 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1934 memory allocation. Likewise, specify preallocated storage for the 1935 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1936 1937 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1938 the figure below we depict these three local rows and all columns (0-11). 1939 1940 .vb 1941 0 1 2 3 4 5 6 7 8 9 10 11 1942 ------------------- 1943 row 3 | o o o d d d o o o o o o 1944 row 4 | o o o d d d o o o o o o 1945 row 5 | o o o d d d o o o o o o 1946 ------------------- 1947 .ve 1948 1949 Thus, any entries in the d locations are stored in the d (diagonal) 1950 submatrix, and any entries in the o locations are stored in the 1951 o (off-diagonal) submatrix. Note that the d and the o submatrices are 1952 stored simply in the MATSEQBAIJ format for compressed row storage. 1953 1954 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 1955 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1956 In general, for PDE problems in which most nonzeros are near the diagonal, 1957 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1958 or you will get TERRIBLE performance; see the users' manual chapter on 1959 matrices. 1960 1961 .keywords: matrix, block, aij, compressed row, sparse, parallel 1962 1963 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateMPIAIJ() 1964 @*/ 1965 int MatCreateMPIBAIJ(MPI_Comm comm,int bs,int m,int n,int M,int N, 1966 int d_nz,int *d_nnz,int o_nz,int *o_nnz,Mat *A) 1967 { 1968 Mat B; 1969 Mat_MPIBAIJ *b; 1970 int ierr, i,sum[2],work[2],mbs,nbs,Mbs=PETSC_DECIDE,Nbs=PETSC_DECIDE,size,flg; 1971 1972 PetscFunctionBegin; 1973 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Invalid block size specified, must be positive"); 1974 1975 MPI_Comm_size(comm,&size); 1976 if (size == 1) { 1977 if (M == PETSC_DECIDE) M = m; 1978 if (N == PETSC_DECIDE) N = n; 1979 ierr = MatCreateSeqBAIJ(comm,bs,M,N,d_nz,d_nnz,A); CHKERRQ(ierr); 1980 PetscFunctionReturn(0); 1981 } 1982 1983 *A = 0; 1984 PetscHeaderCreate(B,_p_Mat,struct _MatOps,MAT_COOKIE,MATMPIBAIJ,comm,MatDestroy,MatView); 1985 PLogObjectCreate(B); 1986 B->data = (void *) (b = PetscNew(Mat_MPIBAIJ)); CHKPTRQ(b); 1987 PetscMemzero(b,sizeof(Mat_MPIBAIJ)); 1988 PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps)); 1989 1990 B->ops->destroy = MatDestroy_MPIBAIJ; 1991 B->ops->view = MatView_MPIBAIJ; 1992 B->mapping = 0; 1993 B->factor = 0; 1994 B->assembled = PETSC_FALSE; 1995 1996 B->insertmode = NOT_SET_VALUES; 1997 MPI_Comm_rank(comm,&b->rank); 1998 MPI_Comm_size(comm,&b->size); 1999 2000 if ( m == PETSC_DECIDE && (d_nnz != PETSC_NULL || o_nnz != PETSC_NULL)) { 2001 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Cannot have PETSC_DECIDE rows but set d_nnz or o_nnz"); 2002 } 2003 if ( M == PETSC_DECIDE && m == PETSC_DECIDE) { 2004 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"either M or m should be specified"); 2005 } 2006 if ( N == PETSC_DECIDE && n == PETSC_DECIDE) { 2007 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"either N or n should be specified"); 2008 } 2009 if ( M != PETSC_DECIDE && m != PETSC_DECIDE) M = PETSC_DECIDE; 2010 if ( N != PETSC_DECIDE && n != PETSC_DECIDE) N = PETSC_DECIDE; 2011 2012 if (M == PETSC_DECIDE || N == PETSC_DECIDE) { 2013 work[0] = m; work[1] = n; 2014 mbs = m/bs; nbs = n/bs; 2015 ierr = MPI_Allreduce( work, sum,2,MPI_INT,MPI_SUM,comm );CHKERRQ(ierr); 2016 if (M == PETSC_DECIDE) {M = sum[0]; Mbs = M/bs;} 2017 if (N == PETSC_DECIDE) {N = sum[1]; Nbs = N/bs;} 2018 } 2019 if (m == PETSC_DECIDE) { 2020 Mbs = M/bs; 2021 if (Mbs*bs != M) SETERRQ(PETSC_ERR_ARG_SIZ,0,"No of global rows must be divisible by blocksize"); 2022 mbs = Mbs/b->size + ((Mbs % b->size) > b->rank); 2023 m = mbs*bs; 2024 } 2025 if (n == PETSC_DECIDE) { 2026 Nbs = N/bs; 2027 if (Nbs*bs != N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"No of global cols must be divisible by blocksize"); 2028 nbs = Nbs/b->size + ((Nbs % b->size) > b->rank); 2029 n = nbs*bs; 2030 } 2031 if (mbs*bs != m || nbs*bs != n) { 2032 SETERRQ(PETSC_ERR_ARG_SIZ,0,"No of local rows, cols must be divisible by blocksize"); 2033 } 2034 2035 b->m = m; B->m = m; 2036 b->n = n; B->n = n; 2037 b->N = N; B->N = N; 2038 b->M = M; B->M = M; 2039 b->bs = bs; 2040 b->bs2 = bs*bs; 2041 b->mbs = mbs; 2042 b->nbs = nbs; 2043 b->Mbs = Mbs; 2044 b->Nbs = Nbs; 2045 2046 /* build local table of row and column ownerships */ 2047 b->rowners = (int *) PetscMalloc(2*(b->size+2)*sizeof(int)); CHKPTRQ(b->rowners); 2048 PLogObjectMemory(B,2*(b->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPIBAIJ)); 2049 b->cowners = b->rowners + b->size + 2; 2050 ierr = MPI_Allgather(&mbs,1,MPI_INT,b->rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2051 b->rowners[0] = 0; 2052 for ( i=2; i<=b->size; i++ ) { 2053 b->rowners[i] += b->rowners[i-1]; 2054 } 2055 b->rstart = b->rowners[b->rank]; 2056 b->rend = b->rowners[b->rank+1]; 2057 b->rstart_bs = b->rstart * bs; 2058 b->rend_bs = b->rend * bs; 2059 2060 ierr = MPI_Allgather(&nbs,1,MPI_INT,b->cowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2061 b->cowners[0] = 0; 2062 for ( i=2; i<=b->size; i++ ) { 2063 b->cowners[i] += b->cowners[i-1]; 2064 } 2065 b->cstart = b->cowners[b->rank]; 2066 b->cend = b->cowners[b->rank+1]; 2067 b->cstart_bs = b->cstart * bs; 2068 b->cend_bs = b->cend * bs; 2069 2070 2071 if (d_nz == PETSC_DEFAULT) d_nz = 5; 2072 ierr = MatCreateSeqBAIJ(PETSC_COMM_SELF,bs,m,n,d_nz,d_nnz,&b->A); CHKERRQ(ierr); 2073 PLogObjectParent(B,b->A); 2074 if (o_nz == PETSC_DEFAULT) o_nz = 0; 2075 ierr = MatCreateSeqBAIJ(PETSC_COMM_SELF,bs,m,N,o_nz,o_nnz,&b->B); CHKERRQ(ierr); 2076 PLogObjectParent(B,b->B); 2077 2078 /* build cache for off array entries formed */ 2079 ierr = StashBuild_Private(&b->stash); CHKERRQ(ierr); 2080 b->donotstash = 0; 2081 b->colmap = 0; 2082 b->garray = 0; 2083 b->roworiented = 1; 2084 2085 /* stuff used in block assembly */ 2086 b->barray = 0; 2087 2088 /* stuff used for matrix vector multiply */ 2089 b->lvec = 0; 2090 b->Mvctx = 0; 2091 2092 /* stuff for MatGetRow() */ 2093 b->rowindices = 0; 2094 b->rowvalues = 0; 2095 b->getrowactive = PETSC_FALSE; 2096 2097 /* hash table stuff */ 2098 b->ht = 0; 2099 b->hd = 0; 2100 b->ht_size = 0; 2101 b->ht_flag = 0; 2102 b->ht_fact = 0; 2103 b->ht_total_ct = 0; 2104 b->ht_insert_ct = 0; 2105 2106 *A = B; 2107 ierr = OptionsHasName(PETSC_NULL,"-mat_use_hash_table",&flg); CHKERRQ(ierr); 2108 if (flg) { 2109 double fact = 1.39; 2110 ierr = MatSetOption(B,MAT_USE_HASH_TABLE); CHKERRQ(ierr); 2111 ierr = OptionsGetDouble(PETSC_NULL,"-mat_use_hash_table",&fact,&flg); CHKERRQ(ierr); 2112 if (fact <= 1.0) fact = 1.39; 2113 ierr = MatMPIBAIJSetHashTableFactor(B,fact); CHKERRQ(ierr); 2114 PLogInfo(0,"MatCreateMPIBAIJ:Hash table Factor used %5.2f\n",fact); 2115 } 2116 PetscFunctionReturn(0); 2117 } 2118 2119 #undef __FUNC__ 2120 #define __FUNC__ "MatConvertSameType_MPIBAIJ" 2121 static int MatConvertSameType_MPIBAIJ(Mat matin,Mat *newmat,int cpvalues) 2122 { 2123 Mat mat; 2124 Mat_MPIBAIJ *a,*oldmat = (Mat_MPIBAIJ *) matin->data; 2125 int ierr, len=0, flg; 2126 2127 PetscFunctionBegin; 2128 *newmat = 0; 2129 PetscHeaderCreate(mat,_p_Mat,struct _MatOps,MAT_COOKIE,MATMPIBAIJ,matin->comm,MatDestroy,MatView); 2130 PLogObjectCreate(mat); 2131 mat->data = (void *) (a = PetscNew(Mat_MPIBAIJ)); CHKPTRQ(a); 2132 PetscMemcpy(mat->ops,&MatOps_Values,sizeof(struct _MatOps)); 2133 mat->ops->destroy = MatDestroy_MPIBAIJ; 2134 mat->ops->view = MatView_MPIBAIJ; 2135 mat->factor = matin->factor; 2136 mat->assembled = PETSC_TRUE; 2137 2138 a->m = mat->m = oldmat->m; 2139 a->n = mat->n = oldmat->n; 2140 a->M = mat->M = oldmat->M; 2141 a->N = mat->N = oldmat->N; 2142 2143 a->bs = oldmat->bs; 2144 a->bs2 = oldmat->bs2; 2145 a->mbs = oldmat->mbs; 2146 a->nbs = oldmat->nbs; 2147 a->Mbs = oldmat->Mbs; 2148 a->Nbs = oldmat->Nbs; 2149 2150 a->rstart = oldmat->rstart; 2151 a->rend = oldmat->rend; 2152 a->cstart = oldmat->cstart; 2153 a->cend = oldmat->cend; 2154 a->size = oldmat->size; 2155 a->rank = oldmat->rank; 2156 mat->insertmode = NOT_SET_VALUES; 2157 a->rowvalues = 0; 2158 a->getrowactive = PETSC_FALSE; 2159 a->barray = 0; 2160 2161 /* hash table stuff */ 2162 a->ht = 0; 2163 a->hd = 0; 2164 a->ht_size = 0; 2165 a->ht_flag = oldmat->ht_flag; 2166 a->ht_fact = oldmat->ht_fact; 2167 a->ht_total_ct = 0; 2168 a->ht_insert_ct = 0; 2169 2170 2171 a->rowners = (int *) PetscMalloc(2*(a->size+2)*sizeof(int)); CHKPTRQ(a->rowners); 2172 PLogObjectMemory(mat,2*(a->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPIBAIJ)); 2173 a->cowners = a->rowners + a->size + 2; 2174 PetscMemcpy(a->rowners,oldmat->rowners,2*(a->size+2)*sizeof(int)); 2175 ierr = StashInitialize_Private(&a->stash); CHKERRQ(ierr); 2176 if (oldmat->colmap) { 2177 a->colmap = (int *) PetscMalloc((a->Nbs)*sizeof(int));CHKPTRQ(a->colmap); 2178 PLogObjectMemory(mat,(a->Nbs)*sizeof(int)); 2179 PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(int)); 2180 } else a->colmap = 0; 2181 if (oldmat->garray && (len = ((Mat_SeqBAIJ *) (oldmat->B->data))->nbs)) { 2182 a->garray = (int *) PetscMalloc(len*sizeof(int)); CHKPTRQ(a->garray); 2183 PLogObjectMemory(mat,len*sizeof(int)); 2184 PetscMemcpy(a->garray,oldmat->garray,len*sizeof(int)); 2185 } else a->garray = 0; 2186 2187 ierr = VecDuplicate(oldmat->lvec,&a->lvec); CHKERRQ(ierr); 2188 PLogObjectParent(mat,a->lvec); 2189 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx); CHKERRQ(ierr); 2190 PLogObjectParent(mat,a->Mvctx); 2191 ierr = MatConvert(oldmat->A,MATSAME,&a->A); CHKERRQ(ierr); 2192 PLogObjectParent(mat,a->A); 2193 ierr = MatConvert(oldmat->B,MATSAME,&a->B); CHKERRQ(ierr); 2194 PLogObjectParent(mat,a->B); 2195 ierr = OptionsHasName(PETSC_NULL,"-help",&flg); CHKERRQ(ierr); 2196 if (flg) { 2197 ierr = MatPrintHelp(mat); CHKERRQ(ierr); 2198 } 2199 *newmat = mat; 2200 PetscFunctionReturn(0); 2201 } 2202 2203 #include "sys.h" 2204 2205 #undef __FUNC__ 2206 #define __FUNC__ "MatLoad_MPIBAIJ" 2207 int MatLoad_MPIBAIJ(Viewer viewer,MatType type,Mat *newmat) 2208 { 2209 Mat A; 2210 int i, nz, ierr, j,rstart, rend, fd; 2211 Scalar *vals,*buf; 2212 MPI_Comm comm = ((PetscObject)viewer)->comm; 2213 MPI_Status status; 2214 int header[4],rank,size,*rowlengths = 0,M,N,m,*rowners,*browners,maxnz,*cols; 2215 int *locrowlens,*sndcounts = 0,*procsnz = 0, jj,*mycols,*ibuf; 2216 int flg,tag = ((PetscObject)viewer)->tag,bs=1,Mbs,mbs,extra_rows; 2217 int *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 2218 int dcount,kmax,k,nzcount,tmp; 2219 2220 PetscFunctionBegin; 2221 ierr = OptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,&flg);CHKERRQ(ierr); 2222 2223 MPI_Comm_size(comm,&size); MPI_Comm_rank(comm,&rank); 2224 if (!rank) { 2225 ierr = ViewerBinaryGetDescriptor(viewer,&fd); CHKERRQ(ierr); 2226 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT); CHKERRQ(ierr); 2227 if (header[0] != MAT_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,0,"not matrix object"); 2228 if (header[3] < 0) { 2229 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,1,"Matrix stored in special format, cannot load as MPIBAIJ"); 2230 } 2231 } 2232 2233 ierr = MPI_Bcast(header+1,3,MPI_INT,0,comm);CHKERRQ(ierr); 2234 M = header[1]; N = header[2]; 2235 2236 if (M != N) SETERRQ(PETSC_ERR_SUP,0,"Can only do square matrices"); 2237 2238 /* 2239 This code adds extra rows to make sure the number of rows is 2240 divisible by the blocksize 2241 */ 2242 Mbs = M/bs; 2243 extra_rows = bs - M + bs*(Mbs); 2244 if (extra_rows == bs) extra_rows = 0; 2245 else Mbs++; 2246 if (extra_rows &&!rank) { 2247 PLogInfo(0,"MatLoad_MPIBAIJ:Padding loaded matrix to match blocksize\n"); 2248 } 2249 2250 /* determine ownership of all rows */ 2251 mbs = Mbs/size + ((Mbs % size) > rank); 2252 m = mbs * bs; 2253 rowners = (int *) PetscMalloc(2*(size+2)*sizeof(int)); CHKPTRQ(rowners); 2254 browners = rowners + size + 1; 2255 ierr = MPI_Allgather(&mbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2256 rowners[0] = 0; 2257 for ( i=2; i<=size; i++ ) rowners[i] += rowners[i-1]; 2258 for ( i=0; i<=size; i++ ) browners[i] = rowners[i]*bs; 2259 rstart = rowners[rank]; 2260 rend = rowners[rank+1]; 2261 2262 /* distribute row lengths to all processors */ 2263 locrowlens = (int*) PetscMalloc( (rend-rstart)*bs*sizeof(int) ); CHKPTRQ(locrowlens); 2264 if (!rank) { 2265 rowlengths = (int*) PetscMalloc( (M+extra_rows)*sizeof(int) ); CHKPTRQ(rowlengths); 2266 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT); CHKERRQ(ierr); 2267 for ( i=0; i<extra_rows; i++ ) rowlengths[M+i] = 1; 2268 sndcounts = (int*) PetscMalloc( size*sizeof(int) ); CHKPTRQ(sndcounts); 2269 for ( i=0; i<size; i++ ) sndcounts[i] = browners[i+1] - browners[i]; 2270 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr); 2271 PetscFree(sndcounts); 2272 } else { 2273 ierr = MPI_Scatterv(0,0,0,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT, 0,comm);CHKERRQ(ierr); 2274 } 2275 2276 if (!rank) { 2277 /* calculate the number of nonzeros on each processor */ 2278 procsnz = (int*) PetscMalloc( size*sizeof(int) ); CHKPTRQ(procsnz); 2279 PetscMemzero(procsnz,size*sizeof(int)); 2280 for ( i=0; i<size; i++ ) { 2281 for ( j=rowners[i]*bs; j< rowners[i+1]*bs; j++ ) { 2282 procsnz[i] += rowlengths[j]; 2283 } 2284 } 2285 PetscFree(rowlengths); 2286 2287 /* determine max buffer needed and allocate it */ 2288 maxnz = 0; 2289 for ( i=0; i<size; i++ ) { 2290 maxnz = PetscMax(maxnz,procsnz[i]); 2291 } 2292 cols = (int *) PetscMalloc( maxnz*sizeof(int) ); CHKPTRQ(cols); 2293 2294 /* read in my part of the matrix column indices */ 2295 nz = procsnz[0]; 2296 ibuf = (int *) PetscMalloc( nz*sizeof(int) ); CHKPTRQ(ibuf); 2297 mycols = ibuf; 2298 if (size == 1) nz -= extra_rows; 2299 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT); CHKERRQ(ierr); 2300 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2301 2302 /* read in every ones (except the last) and ship off */ 2303 for ( i=1; i<size-1; i++ ) { 2304 nz = procsnz[i]; 2305 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT); CHKERRQ(ierr); 2306 ierr = MPI_Send(cols,nz,MPI_INT,i,tag,comm);CHKERRQ(ierr); 2307 } 2308 /* read in the stuff for the last proc */ 2309 if ( size != 1 ) { 2310 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2311 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT); CHKERRQ(ierr); 2312 for ( i=0; i<extra_rows; i++ ) cols[nz+i] = M+i; 2313 ierr = MPI_Send(cols,nz+extra_rows,MPI_INT,size-1,tag,comm);CHKERRQ(ierr); 2314 } 2315 PetscFree(cols); 2316 } else { 2317 /* determine buffer space needed for message */ 2318 nz = 0; 2319 for ( i=0; i<m; i++ ) { 2320 nz += locrowlens[i]; 2321 } 2322 ibuf = (int*) PetscMalloc( nz*sizeof(int) ); CHKPTRQ(ibuf); 2323 mycols = ibuf; 2324 /* receive message of column indices*/ 2325 ierr = MPI_Recv(mycols,nz,MPI_INT,0,tag,comm,&status);CHKERRQ(ierr); 2326 ierr = MPI_Get_count(&status,MPI_INT,&maxnz);CHKERRQ(ierr); 2327 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,0,"something is wrong with file"); 2328 } 2329 2330 /* loop over local rows, determining number of off diagonal entries */ 2331 dlens = (int *) PetscMalloc( 2*(rend-rstart+1)*sizeof(int) ); CHKPTRQ(dlens); 2332 odlens = dlens + (rend-rstart); 2333 mask = (int *) PetscMalloc( 3*Mbs*sizeof(int) ); CHKPTRQ(mask); 2334 PetscMemzero(mask,3*Mbs*sizeof(int)); 2335 masked1 = mask + Mbs; 2336 masked2 = masked1 + Mbs; 2337 rowcount = 0; nzcount = 0; 2338 for ( i=0; i<mbs; i++ ) { 2339 dcount = 0; 2340 odcount = 0; 2341 for ( j=0; j<bs; j++ ) { 2342 kmax = locrowlens[rowcount]; 2343 for ( k=0; k<kmax; k++ ) { 2344 tmp = mycols[nzcount++]/bs; 2345 if (!mask[tmp]) { 2346 mask[tmp] = 1; 2347 if (tmp < rstart || tmp >= rend ) masked2[odcount++] = tmp; 2348 else masked1[dcount++] = tmp; 2349 } 2350 } 2351 rowcount++; 2352 } 2353 2354 dlens[i] = dcount; 2355 odlens[i] = odcount; 2356 2357 /* zero out the mask elements we set */ 2358 for ( j=0; j<dcount; j++ ) mask[masked1[j]] = 0; 2359 for ( j=0; j<odcount; j++ ) mask[masked2[j]] = 0; 2360 } 2361 2362 /* create our matrix */ 2363 ierr = MatCreateMPIBAIJ(comm,bs,m,PETSC_DECIDE,M+extra_rows,N+extra_rows,0,dlens,0,odlens,newmat); 2364 CHKERRQ(ierr); 2365 A = *newmat; 2366 MatSetOption(A,MAT_COLUMNS_SORTED); 2367 2368 if (!rank) { 2369 buf = (Scalar *) PetscMalloc( maxnz*sizeof(Scalar) ); CHKPTRQ(buf); 2370 /* read in my part of the matrix numerical values */ 2371 nz = procsnz[0]; 2372 vals = buf; 2373 mycols = ibuf; 2374 if (size == 1) nz -= extra_rows; 2375 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR); CHKERRQ(ierr); 2376 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2377 2378 /* insert into matrix */ 2379 jj = rstart*bs; 2380 for ( i=0; i<m; i++ ) { 2381 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2382 mycols += locrowlens[i]; 2383 vals += locrowlens[i]; 2384 jj++; 2385 } 2386 /* read in other processors (except the last one) and ship out */ 2387 for ( i=1; i<size-1; i++ ) { 2388 nz = procsnz[i]; 2389 vals = buf; 2390 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR); CHKERRQ(ierr); 2391 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 2392 } 2393 /* the last proc */ 2394 if ( size != 1 ){ 2395 nz = procsnz[i] - extra_rows; 2396 vals = buf; 2397 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR); CHKERRQ(ierr); 2398 for ( i=0; i<extra_rows; i++ ) vals[nz+i] = 1.0; 2399 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,A->tag,comm);CHKERRQ(ierr); 2400 } 2401 PetscFree(procsnz); 2402 } else { 2403 /* receive numeric values */ 2404 buf = (Scalar*) PetscMalloc( nz*sizeof(Scalar) ); CHKPTRQ(buf); 2405 2406 /* receive message of values*/ 2407 vals = buf; 2408 mycols = ibuf; 2409 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 2410 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2411 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,0,"something is wrong with file"); 2412 2413 /* insert into matrix */ 2414 jj = rstart*bs; 2415 for ( i=0; i<m; i++ ) { 2416 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2417 mycols += locrowlens[i]; 2418 vals += locrowlens[i]; 2419 jj++; 2420 } 2421 } 2422 PetscFree(locrowlens); 2423 PetscFree(buf); 2424 PetscFree(ibuf); 2425 PetscFree(rowners); 2426 PetscFree(dlens); 2427 PetscFree(mask); 2428 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 2429 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 2430 PetscFunctionReturn(0); 2431 } 2432 2433 2434 2435 #undef __FUNC__ 2436 #define __FUNC__ "MatMPIBAIJSetHashTableFactor" 2437 /*@ 2438 MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2439 2440 Input Parameters: 2441 . mat - the matrix 2442 . fact - factor 2443 2444 Collective on Mat 2445 2446 Notes: 2447 This can also be set by the command line option: -mat_use_hash_table fact 2448 2449 .keywords: matrix, hashtable, factor, HT 2450 2451 .seealso: MatSetOption() 2452 @*/ 2453 int MatMPIBAIJSetHashTableFactor(Mat mat,double fact) 2454 { 2455 Mat_MPIBAIJ *baij; 2456 2457 PetscFunctionBegin; 2458 PetscValidHeaderSpecific(mat,MAT_COOKIE); 2459 if (mat->type != MATMPIBAIJ) { 2460 SETERRQ(PETSC_ERR_ARG_WRONG,1,"Incorrect matrix type. Use MPIBAIJ only."); 2461 } 2462 baij = (Mat_MPIBAIJ*) mat->data; 2463 baij->ht_fact = fact; 2464 PetscFunctionReturn(0); 2465 } 2466