1 /*$Id: mpisbaij.c,v 1.38 2000/11/28 17:29:39 bsmith Exp bsmith $*/ 2 3 #include "src/mat/impls/baij/mpi/mpibaij.h" /*I "petscmat.h" I*/ 4 #include "src/vec/vecimpl.h" 5 #include "mpisbaij.h" 6 #include "src/mat/impls/sbaij/seq/sbaij.h" 7 8 extern int MatSetUpMultiply_MPISBAIJ(Mat); 9 extern int DisAssemble_MPISBAIJ(Mat); 10 extern int MatIncreaseOverlap_MPISBAIJ(Mat,int,IS *,int); 11 extern int MatGetSubMatrices_MPISBAIJ(Mat,int,IS *,IS *,MatReuse,Mat **); 12 extern int MatGetValues_SeqSBAIJ(Mat,int,int *,int,int *,Scalar *); 13 extern int MatSetValues_SeqSBAIJ(Mat,int,int *,int,int *,Scalar *,InsertMode); 14 extern int MatSetValuesBlocked_SeqSBAIJ(Mat,int,int*,int,int*,Scalar*,InsertMode); 15 extern int MatGetRow_SeqSBAIJ(Mat,int,int*,int**,Scalar**); 16 extern int MatRestoreRow_SeqSBAIJ(Mat,int,int*,int**,Scalar**); 17 extern int MatPrintHelp_SeqSBAIJ(Mat); 18 extern int MatZeroRows_SeqSBAIJ(Mat,IS,Scalar*); 19 extern int MatZeroRows_SeqBAIJ(Mat,IS,Scalar *); 20 extern int MatGetRowMax_MPISBAIJ(Mat,Vec); 21 22 /* UGLY, ugly, ugly 23 When MatScalar == Scalar the function MatSetValuesBlocked_MPIBAIJ_MatScalar() does 24 not exist. Otherwise ..._MatScalar() takes matrix elements in single precision and 25 inserts them into the single precision data structure. The function MatSetValuesBlocked_MPIBAIJ() 26 converts the entries into single precision and then calls ..._MatScalar() to put them 27 into the single precision data structures. 28 */ 29 #if defined(PETSC_USE_MAT_SINGLE) 30 extern int MatSetValuesBlocked_SeqSBAIJ_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode); 31 extern int MatSetValues_MPISBAIJ_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode); 32 extern int MatSetValuesBlocked_MPISBAIJ_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode); 33 extern int MatSetValues_MPISBAIJ_HT_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode); 34 extern int MatSetValuesBlocked_MPISBAIJ_HT_MatScalar(Mat,int,int*,int,int*,MatScalar*,InsertMode); 35 #else 36 #define MatSetValuesBlocked_SeqSBAIJ_MatScalar MatSetValuesBlocked_SeqSBAIJ 37 #define MatSetValues_MPISBAIJ_MatScalar MatSetValues_MPISBAIJ 38 #define MatSetValuesBlocked_MPISBAIJ_MatScalar MatSetValuesBlocked_MPISBAIJ 39 #define MatSetValues_MPISBAIJ_HT_MatScalar MatSetValues_MPISBAIJ_HT 40 #define MatSetValuesBlocked_MPISBAIJ_HT_MatScalar MatSetValuesBlocked_MPISBAIJ_HT 41 #endif 42 43 EXTERN_C_BEGIN 44 #undef __FUNC__ 45 #define __FUNC__ "MatStoreValues_MPISBAIJ" 46 int MatStoreValues_MPISBAIJ(Mat mat) 47 { 48 Mat_MPISBAIJ *aij = (Mat_MPISBAIJ *)mat->data; 49 int ierr; 50 51 PetscFunctionBegin; 52 ierr = MatStoreValues(aij->A);CHKERRQ(ierr); 53 ierr = MatStoreValues(aij->B);CHKERRQ(ierr); 54 PetscFunctionReturn(0); 55 } 56 EXTERN_C_END 57 58 EXTERN_C_BEGIN 59 #undef __FUNC__ 60 #define __FUNC__ "MatRetrieveValues_MPISBAIJ" 61 int MatRetrieveValues_MPISBAIJ(Mat mat) 62 { 63 Mat_MPISBAIJ *aij = (Mat_MPISBAIJ *)mat->data; 64 int ierr; 65 66 PetscFunctionBegin; 67 ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr); 68 ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr); 69 PetscFunctionReturn(0); 70 } 71 EXTERN_C_END 72 73 /* 74 Local utility routine that creates a mapping from the global column 75 number to the local number in the off-diagonal part of the local 76 storage of the matrix. This is done in a non scable way since the 77 length of colmap equals the global matrix length. 78 */ 79 #undef __FUNC__ 80 #define __FUNC__ "CreateColmap_MPISBAIJ_Private" 81 static int CreateColmap_MPISBAIJ_Private(Mat mat) 82 { 83 PetscFunctionBegin; 84 SETERRQ(1,"Function not yet written for SBAIJ format"); 85 /* PetscFunctionReturn(0); */ 86 } 87 88 #define CHUNKSIZE 10 89 90 #define MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv) \ 91 { \ 92 \ 93 brow = row/bs; \ 94 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 95 rmax = aimax[brow]; nrow = ailen[brow]; \ 96 bcol = col/bs; \ 97 ridx = row % bs; cidx = col % bs; \ 98 low = 0; high = nrow; \ 99 while (high-low > 3) { \ 100 t = (low+high)/2; \ 101 if (rp[t] > bcol) high = t; \ 102 else low = t; \ 103 } \ 104 for (_i=low; _i<high; _i++) { \ 105 if (rp[_i] > bcol) break; \ 106 if (rp[_i] == bcol) { \ 107 bap = ap + bs2*_i + bs*cidx + ridx; \ 108 if (addv == ADD_VALUES) *bap += value; \ 109 else *bap = value; \ 110 goto a_noinsert; \ 111 } \ 112 } \ 113 if (a->nonew == 1) goto a_noinsert; \ 114 else if (a->nonew == -1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero into matrix"); \ 115 if (nrow >= rmax) { \ 116 /* there is no extra room in row, therefore enlarge */ \ 117 int new_nz = ai[a->mbs] + CHUNKSIZE,len,*new_i,*new_j; \ 118 MatScalar *new_a; \ 119 \ 120 if (a->nonew == -2) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); \ 121 \ 122 /* malloc new storage space */ \ 123 len = new_nz*(sizeof(int)+bs2*sizeof(MatScalar))+(a->mbs+1)*sizeof(int); \ 124 ierr = PetscMalloc(len,&( new_a ));CHKERRQ(ierr); \ 125 new_j = (int*)(new_a + bs2*new_nz); \ 126 new_i = new_j + new_nz; \ 127 \ 128 /* copy over old data into new slots */ \ 129 for (ii=0; ii<brow+1; ii++) {new_i[ii] = ai[ii];} \ 130 for (ii=brow+1; ii<a->mbs+1; ii++) {new_i[ii] = ai[ii]+CHUNKSIZE;} \ 131 ierr = PetscMemcpy(new_j,aj,(ai[brow]+nrow)*sizeof(int));CHKERRQ(ierr); \ 132 len = (new_nz - CHUNKSIZE - ai[brow] - nrow); \ 133 ierr = PetscMemcpy(new_j+ai[brow]+nrow+CHUNKSIZE,aj+ai[brow]+nrow,len*sizeof(int));CHKERRQ(ierr); \ 134 ierr = PetscMemcpy(new_a,aa,(ai[brow]+nrow)*bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 135 ierr = PetscMemzero(new_a+bs2*(ai[brow]+nrow),bs2*CHUNKSIZE*sizeof(Scalar));CHKERRQ(ierr); \ 136 ierr = PetscMemcpy(new_a+bs2*(ai[brow]+nrow+CHUNKSIZE), \ 137 aa+bs2*(ai[brow]+nrow),bs2*len*sizeof(MatScalar));CHKERRQ(ierr); \ 138 /* free up old matrix storage */ \ 139 ierr = PetscFree(a->a);CHKERRQ(ierr); \ 140 if (!a->singlemalloc) { \ 141 ierr = PetscFree(a->i);CHKERRQ(ierr); \ 142 ierr = PetscFree(a->j);CHKERRQ(ierr);\ 143 } \ 144 aa = a->a = new_a; ai = a->i = new_i; aj = a->j = new_j; \ 145 a->singlemalloc = PETSC_TRUE; \ 146 \ 147 rp = aj + ai[brow]; ap = aa + bs2*ai[brow]; \ 148 rmax = aimax[brow] = aimax[brow] + CHUNKSIZE; \ 149 PetscLogObjectMemory(A,CHUNKSIZE*(sizeof(int) + bs2*sizeof(MatScalar))); \ 150 a->s_maxnz += bs2*CHUNKSIZE; \ 151 a->reallocs++; \ 152 a->s_nz++; \ 153 } \ 154 N = nrow++ - 1; \ 155 /* shift up all the later entries in this row */ \ 156 for (ii=N; ii>=_i; ii--) { \ 157 rp[ii+1] = rp[ii]; \ 158 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 159 } \ 160 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); } \ 161 rp[_i] = bcol; \ 162 ap[bs2*_i + bs*cidx + ridx] = value; \ 163 a_noinsert:; \ 164 ailen[brow] = nrow; \ 165 } 166 #ifndef MatSetValues_SeqBAIJ_B_Private 167 #define MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv) \ 168 { \ 169 brow = row/bs; \ 170 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 171 rmax = bimax[brow]; nrow = bilen[brow]; \ 172 bcol = col/bs; \ 173 ridx = row % bs; cidx = col % bs; \ 174 low = 0; high = nrow; \ 175 while (high-low > 3) { \ 176 t = (low+high)/2; \ 177 if (rp[t] > bcol) high = t; \ 178 else low = t; \ 179 } \ 180 for (_i=low; _i<high; _i++) { \ 181 if (rp[_i] > bcol) break; \ 182 if (rp[_i] == bcol) { \ 183 bap = ap + bs2*_i + bs*cidx + ridx; \ 184 if (addv == ADD_VALUES) *bap += value; \ 185 else *bap = value; \ 186 goto b_noinsert; \ 187 } \ 188 } \ 189 if (b->nonew == 1) goto b_noinsert; \ 190 else if (b->nonew == -1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero into matrix"); \ 191 if (nrow >= rmax) { \ 192 /* there is no extra room in row, therefore enlarge */ \ 193 int new_nz = bi[b->mbs] + CHUNKSIZE,len,*new_i,*new_j; \ 194 MatScalar *new_a; \ 195 \ 196 if (b->nonew == -2) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); \ 197 \ 198 /* malloc new storage space */ \ 199 len = new_nz*(sizeof(int)+bs2*sizeof(MatScalar))+(b->mbs+1)*sizeof(int); \ 200 ierr = PetscMalloc(len,&( new_a ));CHKERRQ(ierr); \ 201 new_j = (int*)(new_a + bs2*new_nz); \ 202 new_i = new_j + new_nz; \ 203 \ 204 /* copy over old data into new slots */ \ 205 for (ii=0; ii<brow+1; ii++) {new_i[ii] = bi[ii];} \ 206 for (ii=brow+1; ii<b->mbs+1; ii++) {new_i[ii] = bi[ii]+CHUNKSIZE;} \ 207 ierr = PetscMemcpy(new_j,bj,(bi[brow]+nrow)*sizeof(int));CHKERRQ(ierr); \ 208 len = (new_nz - CHUNKSIZE - bi[brow] - nrow); \ 209 ierr = PetscMemcpy(new_j+bi[brow]+nrow+CHUNKSIZE,bj+bi[brow]+nrow,len*sizeof(int));CHKERRQ(ierr); \ 210 ierr = PetscMemcpy(new_a,ba,(bi[brow]+nrow)*bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 211 ierr = PetscMemzero(new_a+bs2*(bi[brow]+nrow),bs2*CHUNKSIZE*sizeof(MatScalar));CHKERRQ(ierr); \ 212 ierr = PetscMemcpy(new_a+bs2*(bi[brow]+nrow+CHUNKSIZE), \ 213 ba+bs2*(bi[brow]+nrow),bs2*len*sizeof(MatScalar));CHKERRQ(ierr); \ 214 /* free up old matrix storage */ \ 215 ierr = PetscFree(b->a);CHKERRQ(ierr); \ 216 if (!b->singlemalloc) { \ 217 ierr = PetscFree(b->i);CHKERRQ(ierr); \ 218 ierr = PetscFree(b->j);CHKERRQ(ierr); \ 219 } \ 220 ba = b->a = new_a; bi = b->i = new_i; bj = b->j = new_j; \ 221 b->singlemalloc = PETSC_TRUE; \ 222 \ 223 rp = bj + bi[brow]; ap = ba + bs2*bi[brow]; \ 224 rmax = bimax[brow] = bimax[brow] + CHUNKSIZE; \ 225 PetscLogObjectMemory(B,CHUNKSIZE*(sizeof(int) + bs2*sizeof(MatScalar))); \ 226 b->maxnz += bs2*CHUNKSIZE; \ 227 b->reallocs++; \ 228 b->nz++; \ 229 } \ 230 N = nrow++ - 1; \ 231 /* shift up all the later entries in this row */ \ 232 for (ii=N; ii>=_i; ii--) { \ 233 rp[ii+1] = rp[ii]; \ 234 ierr = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \ 235 } \ 236 if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);} \ 237 rp[_i] = bcol; \ 238 ap[bs2*_i + bs*cidx + ridx] = value; \ 239 b_noinsert:; \ 240 bilen[brow] = nrow; \ 241 } 242 #endif 243 244 #if defined(PETSC_USE_MAT_SINGLE) 245 #undef __FUNC__ 246 #define __FUNC__ "MatSetValues_MPISBAIJ" 247 int MatSetValues_MPISBAIJ(Mat mat,int m,int *im,int n,int *in,Scalar *v,InsertMode addv) 248 { 249 Mat_MPISBAIJ *b = (Mat_MPISBAIJ*)mat->data; 250 int ierr,i,N = m*n; 251 MatScalar *vsingle; 252 253 PetscFunctionBegin; 254 if (N > b->setvalueslen) { 255 if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);} 256 ierr = PetscMalloc(N*sizeof(MatScalar),&( b->setvaluescopy ));CHKERRQ(ierr); 257 b->setvalueslen = N; 258 } 259 vsingle = b->setvaluescopy; 260 261 for (i=0; i<N; i++) { 262 vsingle[i] = v[i]; 263 } 264 ierr = MatSetValues_MPISBAIJ_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr); 265 PetscFunctionReturn(0); 266 } 267 268 #undef __FUNC__ 269 #define __FUNC__ "MatSetValuesBlocked_MPISBAIJ" 270 int MatSetValuesBlocked_MPISBAIJ(Mat mat,int m,int *im,int n,int *in,Scalar *v,InsertMode addv) 271 { 272 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 273 int ierr,i,N = m*n*b->bs2; 274 MatScalar *vsingle; 275 276 PetscFunctionBegin; 277 if (N > b->setvalueslen) { 278 if (b->setvaluescopy) {ierr = PetscFree(b->setvaluescopy);CHKERRQ(ierr);} 279 ierr = PetscMalloc(N*sizeof(MatScalar),&( b->setvaluescopy ));CHKERRQ(ierr); 280 b->setvalueslen = N; 281 } 282 vsingle = b->setvaluescopy; 283 for (i=0; i<N; i++) { 284 vsingle[i] = v[i]; 285 } 286 ierr = MatSetValuesBlocked_MPISBAIJ_MatScalar(mat,m,im,n,in,vsingle,addv);CHKERRQ(ierr); 287 PetscFunctionReturn(0); 288 } 289 290 #undef __FUNC__ 291 #define __FUNC__ "MatSetValues_MPISBAIJ_HT" 292 int MatSetValues_MPISBAIJ_HT(Mat mat,int m,int *im,int n,int *in,Scalar *v,InsertMode addv) 293 { 294 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 295 int ierr,i,N = m*n; 296 MatScalar *vsingle; 297 298 PetscFunctionBegin; 299 SETERRQ(1,"Function not yet written for SBAIJ format"); 300 /* PetscFunctionReturn(0); */ 301 } 302 303 #undef __FUNC__ 304 #define __FUNC__ "MatSetValuesBlocked_MPISBAIJ_HT" 305 int MatSetValuesBlocked_MPISBAIJ_HT(Mat mat,int m,int *im,int n,int *in,Scalar *v,InsertMode addv) 306 { 307 Mat_MPIBAIJ *b = (Mat_MPIBAIJ*)mat->data; 308 int ierr,i,N = m*n*b->bs2; 309 MatScalar *vsingle; 310 311 PetscFunctionBegin; 312 SETERRQ(1,"Function not yet written for SBAIJ format"); 313 /* PetscFunctionReturn(0); */ 314 } 315 #endif 316 317 /* Only add/insert a(i,j) with i<=j (blocks). 318 Any a(i,j) with i>j input by user is ingored. 319 */ 320 #undef __FUNC__ 321 #define __FUNC__ "MatSetValues_MPIBAIJ" 322 int MatSetValues_MPISBAIJ_MatScalar(Mat mat,int m,int *im,int n,int *in,MatScalar *v,InsertMode addv) 323 { 324 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 325 MatScalar value; 326 PetscTruth roworiented = baij->roworiented; 327 int ierr,i,j,row,col; 328 int rstart_orig=baij->rstart_bs; 329 int rend_orig=baij->rend_bs,cstart_orig=baij->cstart_bs; 330 int cend_orig=baij->cend_bs,bs=baij->bs; 331 332 /* Some Variables required in the macro */ 333 Mat A = baij->A; 334 Mat_SeqSBAIJ *a = (Mat_SeqSBAIJ*)(A)->data; 335 int *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j; 336 MatScalar *aa=a->a; 337 338 Mat B = baij->B; 339 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(B)->data; 340 int *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j; 341 MatScalar *ba=b->a; 342 343 int *rp,ii,nrow,_i,rmax,N,brow,bcol; 344 int low,high,t,ridx,cidx,bs2=a->bs2; 345 MatScalar *ap,*bap; 346 347 /* for stash */ 348 int n_loc, *in_loc=0; 349 MatScalar *v_loc=0; 350 351 PetscFunctionBegin; 352 353 if(!baij->donotstash){ 354 ierr = PetscMalloc(n*sizeof(int),&( in_loc ));CHKERRQ(ierr); 355 ierr = PetscMalloc(n*sizeof(MatScalar),&( v_loc ));CHKERRQ(ierr); 356 } 357 358 for (i=0; i<m; i++) { 359 if (im[i] < 0) continue; 360 #if defined(PETSC_USE_BOPT_g) 361 if (im[i] >= mat->M) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 362 #endif 363 if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */ 364 row = im[i] - rstart_orig; /* local row index */ 365 for (j=0; j<n; j++) { 366 if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */ 367 if (in[j] >= cstart_orig && in[j] < cend_orig){ /* diag entry (A) */ 368 col = in[j] - cstart_orig; /* local col index */ 369 brow = row/bs; bcol = col/bs; 370 if (brow > bcol) continue; /* ignore lower triangular blocks of A */ 371 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 372 MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv); 373 /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 374 } else if (in[j] < 0) continue; 375 #if defined(PETSC_USE_BOPT_g) 376 else if (in[j] >= mat->N) {SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Col too large");} 377 #endif 378 else { /* off-diag entry (B) */ 379 if (mat->was_assembled) { 380 if (!baij->colmap) { 381 ierr = CreateColmap_MPISBAIJ_Private(mat);CHKERRQ(ierr); 382 } 383 #if defined (PETSC_USE_CTABLE) 384 ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr); 385 col = col - 1 + in[j]%bs; 386 #else 387 col = baij->colmap[in[j]/bs] - 1 + in[j]%bs; 388 #endif 389 if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) { 390 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 391 col = in[j]; 392 /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */ 393 B = baij->B; 394 b = (Mat_SeqBAIJ*)(B)->data; 395 bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j; 396 ba=b->a; 397 } 398 } else col = in[j]; 399 if (roworiented) value = v[i*n+j]; else value = v[i+j*m]; 400 MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv); 401 /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */ 402 } 403 } 404 } else { /* off processor entry */ 405 if (!baij->donotstash) { 406 n_loc = 0; 407 for (j=0; j<n; j++){ 408 if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */ 409 in_loc[n_loc] = in[j]; 410 if (roworiented) { 411 v_loc[n_loc] = v[i*n+j]; 412 } else { 413 v_loc[n_loc] = v[j*m+i]; 414 } 415 n_loc++; 416 } 417 ierr = MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc);CHKERRQ(ierr); 418 } 419 } 420 } 421 422 if(!baij->donotstash){ 423 ierr = PetscFree(in_loc);CHKERRQ(ierr); 424 ierr = PetscFree(v_loc);CHKERRQ(ierr); 425 } 426 PetscFunctionReturn(0); 427 } 428 429 #undef __FUNC__ 430 #define __FUNC__ "MatSetValuesBlocked_MPISBAIJ" 431 int MatSetValuesBlocked_MPISBAIJ_MatScalar(Mat mat,int m,int *im,int n,int *in,MatScalar *v,InsertMode addv) 432 { 433 PetscFunctionBegin; 434 SETERRQ(1,"Function not yet written for SBAIJ format"); 435 /* PetscFunctionReturn(0); */ 436 } 437 438 #define HASH_KEY 0.6180339887 439 #define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(int)((size)*(tmp-(int)tmp))) 440 /* #define HASH(size,key) ((int)((size)*fmod(((key)*HASH_KEY),1))) */ 441 /* #define HASH(size,key,tmp) ((int)((size)*fmod(((key)*HASH_KEY),1))) */ 442 #undef __FUNC__ 443 #define __FUNC__ "MatSetValues_MPISBAIJ_HT_MatScalar" 444 int MatSetValues_MPISBAIJ_HT_MatScalar(Mat mat,int m,int *im,int n,int *in,MatScalar *v,InsertMode addv) 445 { 446 PetscFunctionBegin; 447 SETERRQ(1,"Function not yet written for SBAIJ format"); 448 /* PetscFunctionReturn(0); */ 449 } 450 451 #undef __FUNC__ 452 #define __FUNC__ "MatSetValuesBlocked_MPISBAIJ_HT_MatScalar" 453 int MatSetValuesBlocked_MPISBAIJ_HT_MatScalar(Mat mat,int m,int *im,int n,int *in,MatScalar *v,InsertMode addv) 454 { 455 PetscFunctionBegin; 456 SETERRQ(1,"Function not yet written for SBAIJ format"); 457 /* PetscFunctionReturn(0); */ 458 } 459 460 #undef __FUNC__ 461 #define __FUNC__ "MatGetValues_MPISBAIJ" 462 int MatGetValues_MPISBAIJ(Mat mat,int m,int *idxm,int n,int *idxn,Scalar *v) 463 { 464 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 465 int bs=baij->bs,ierr,i,j,bsrstart = baij->rstart*bs,bsrend = baij->rend*bs; 466 int bscstart = baij->cstart*bs,bscend = baij->cend*bs,row,col,data; 467 468 PetscFunctionBegin; 469 for (i=0; i<m; i++) { 470 if (idxm[i] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); 471 if (idxm[i] >= mat->M) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 472 if (idxm[i] >= bsrstart && idxm[i] < bsrend) { 473 row = idxm[i] - bsrstart; 474 for (j=0; j<n; j++) { 475 if (idxn[j] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Negative column"); 476 if (idxn[j] >= mat->N) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 477 if (idxn[j] >= bscstart && idxn[j] < bscend){ 478 col = idxn[j] - bscstart; 479 ierr = MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 480 } else { 481 if (!baij->colmap) { 482 ierr = CreateColmap_MPISBAIJ_Private(mat);CHKERRQ(ierr); 483 } 484 #if defined (PETSC_USE_CTABLE) 485 ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr); 486 data --; 487 #else 488 data = baij->colmap[idxn[j]/bs]-1; 489 #endif 490 if((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0; 491 else { 492 col = data + idxn[j]%bs; 493 ierr = MatGetValues_SeqSBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr); 494 } 495 } 496 } 497 } else { 498 SETERRQ(PETSC_ERR_SUP,"Only local values currently supported"); 499 } 500 } 501 PetscFunctionReturn(0); 502 } 503 504 #undef __FUNC__ 505 #define __FUNC__ "MatNorm_MPISBAIJ" 506 int MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm) 507 { 508 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 509 /* Mat_SeqSBAIJ *amat = (Mat_SeqSBAIJ*)baij->A->data; */ 510 /* Mat_SeqBAIJ *bmat = (Mat_SeqBAIJ*)baij->B->data; */ 511 int ierr; 512 PetscReal sum[2],*lnorm2; 513 514 PetscFunctionBegin; 515 if (baij->size == 1) { 516 ierr = MatNorm(baij->A,type,norm);CHKERRQ(ierr); 517 } else { 518 if (type == NORM_FROBENIUS) { 519 ierr = PetscMalloc(2*sizeof(double),&( lnorm2 ));CHKERRQ(ierr); 520 ierr = MatNorm(baij->A,type,lnorm2);CHKERRQ(ierr); 521 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++; /* squar power of norm(A) */ 522 ierr = MatNorm(baij->B,type,lnorm2);CHKERRQ(ierr); 523 *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--; /* squar power of norm(B) */ 524 /* 525 ierr = MPI_Comm_rank(PETSC_COMM_WORLD,&rank);CHKERRQ(ierr); 526 PetscSynchronizedPrintf(PETSC_COMM_WORLD,"[%d], lnorm2=%g, %g\n",rank,lnorm2[0],lnorm2[1]); 527 */ 528 ierr = MPI_Allreduce(lnorm2,&sum,2,MPI_DOUBLE,MPI_SUM,mat->comm);CHKERRQ(ierr); 529 /* 530 PetscSynchronizedPrintf(PETSC_COMM_WORLD,"[%d], sum=%g, %g\n",rank,sum[0],sum[1]); 531 PetscSynchronizedFlush(PETSC_COMM_WORLD); */ 532 533 *norm = sqrt(sum[0] + 2*sum[1]); 534 ierr = PetscFree(lnorm2);CHKERRQ(ierr); 535 } else { 536 SETERRQ(PETSC_ERR_SUP,"No support for this norm yet"); 537 } 538 } 539 PetscFunctionReturn(0); 540 } 541 542 /* 543 Creates the hash table, and sets the table 544 This table is created only once. 545 If new entried need to be added to the matrix 546 then the hash table has to be destroyed and 547 recreated. 548 */ 549 #undef __FUNC__ 550 #define __FUNC__ "MatCreateHashTable_MPISBAIJ_Private" 551 int MatCreateHashTable_MPISBAIJ_Private(Mat mat,PetscReal factor) 552 { 553 PetscFunctionBegin; 554 SETERRQ(1,"Function not yet written for SBAIJ format"); 555 /* PetscFunctionReturn(0); */ 556 } 557 558 #undef __FUNC__ 559 #define __FUNC__ "MatAssemblyBegin_MPISBAIJ" 560 int MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode) 561 { 562 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 563 int ierr,nstash,reallocs; 564 InsertMode addv; 565 566 PetscFunctionBegin; 567 if (baij->donotstash) { 568 PetscFunctionReturn(0); 569 } 570 571 /* make sure all processors are either in INSERTMODE or ADDMODE */ 572 ierr = MPI_Allreduce(&mat->insertmode,&addv,1,MPI_INT,MPI_BOR,mat->comm);CHKERRQ(ierr); 573 if (addv == (ADD_VALUES|INSERT_VALUES)) { 574 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added"); 575 } 576 mat->insertmode = addv; /* in case this processor had no cache */ 577 578 ierr = MatStashScatterBegin_Private(&mat->stash,baij->rowners_bs);CHKERRQ(ierr); 579 ierr = MatStashScatterBegin_Private(&mat->bstash,baij->rowners);CHKERRQ(ierr); 580 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 581 PetscLogInfo(0,"MatAssemblyBegin_MPISBAIJ:Stash has %d entries,uses %d mallocs.\n",nstash,reallocs); 582 ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr); 583 PetscLogInfo(0,"MatAssemblyBegin_MPISBAIJ:Block-Stash has %d entries, uses %d mallocs.\n",nstash,reallocs); 584 PetscFunctionReturn(0); 585 } 586 587 #undef __FUNC__ 588 #define __FUNC__ "MatAssemblyEnd_MPISBAIJ" 589 int MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode) 590 { 591 Mat_MPISBAIJ *baij=(Mat_MPISBAIJ*)mat->data; 592 Mat_SeqSBAIJ *a=(Mat_SeqSBAIJ*)baij->A->data; 593 Mat_SeqBAIJ *b=(Mat_SeqBAIJ*)baij->B->data; 594 int i,j,rstart,ncols,n,ierr,flg,bs2=baij->bs2; 595 int *row,*col,other_disassembled; 596 PetscTruth r1,r2,r3; 597 MatScalar *val; 598 InsertMode addv = mat->insertmode; 599 int rank; 600 601 PetscFunctionBegin; 602 /* remove 2 line below later */ 603 ierr = MPI_Comm_rank(PETSC_COMM_WORLD, &rank);CHKERRQ(ierr); 604 605 if (!baij->donotstash) { 606 while (1) { 607 ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 608 /* 609 PetscSynchronizedPrintf(PETSC_COMM_WORLD,"[%d]: in AssemblyEnd, stash, flg=%d\n",rank,flg); 610 PetscSynchronizedFlush(PETSC_COMM_WORLD); 611 */ 612 if (!flg) break; 613 614 for (i=0; i<n;) { 615 /* Now identify the consecutive vals belonging to the same row */ 616 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 617 if (j < n) ncols = j-i; 618 else ncols = n-i; 619 /* Now assemble all these values with a single function call */ 620 ierr = MatSetValues_MPISBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr); 621 i = j; 622 } 623 } 624 ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr); 625 /* Now process the block-stash. Since the values are stashed column-oriented, 626 set the roworiented flag to column oriented, and after MatSetValues() 627 restore the original flags */ 628 r1 = baij->roworiented; 629 r2 = a->roworiented; 630 r3 = b->roworiented; 631 baij->roworiented = PETSC_FALSE; 632 a->roworiented = PETSC_FALSE; 633 b->roworiented = PETSC_FALSE; 634 while (1) { 635 ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr); 636 if (!flg) break; 637 638 for (i=0; i<n;) { 639 /* Now identify the consecutive vals belonging to the same row */ 640 for (j=i,rstart=row[j]; j<n; j++) { if (row[j] != rstart) break; } 641 if (j < n) ncols = j-i; 642 else ncols = n-i; 643 ierr = MatSetValuesBlocked_MPISBAIJ_MatScalar(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr); 644 i = j; 645 } 646 } 647 ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr); 648 baij->roworiented = r1; 649 a->roworiented = r2; 650 b->roworiented = r3; 651 } 652 653 ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr); 654 ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr); 655 656 /* determine if any processor has disassembled, if so we must 657 also disassemble ourselfs, in order that we may reassemble. */ 658 /* 659 if nonzero structure of submatrix B cannot change then we know that 660 no processor disassembled thus we can skip this stuff 661 */ 662 if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) { 663 ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPI_INT,MPI_PROD,mat->comm);CHKERRQ(ierr); 664 if (mat->was_assembled && !other_disassembled) { 665 ierr = DisAssemble_MPISBAIJ(mat);CHKERRQ(ierr); 666 } 667 } 668 669 if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) { 670 ierr = MatSetUpMultiply_MPISBAIJ(mat);CHKERRQ(ierr); 671 } 672 ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr); 673 ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr); 674 675 #if defined(PETSC_USE_BOPT_g) 676 if (baij->ht && mode== MAT_FINAL_ASSEMBLY) { 677 PetscLogInfo(0,"MatAssemblyEnd_MPISBAIJ:Average Hash Table Search in MatSetValues = %5.2f\n",((double)baij->ht_total_ct)/baij->ht_insert_ct); 678 baij->ht_total_ct = 0; 679 baij->ht_insert_ct = 0; 680 } 681 #endif 682 if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) { 683 ierr = MatCreateHashTable_MPISBAIJ_Private(mat,baij->ht_fact);CHKERRQ(ierr); 684 mat->ops->setvalues = MatSetValues_MPISBAIJ_HT; 685 mat->ops->setvaluesblocked = MatSetValuesBlocked_MPISBAIJ_HT; 686 } 687 688 if (baij->rowvalues) { 689 ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr); 690 baij->rowvalues = 0; 691 } 692 PetscFunctionReturn(0); 693 } 694 695 #undef __FUNC__ 696 #define __FUNC__ "MatView_MPISBAIJ_ASCIIorDraworSocket" 697 static int MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer) 698 { 699 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 700 int ierr,format,bs = baij->bs,size = baij->size,rank = baij->rank; 701 PetscTruth isascii,isdraw; 702 PetscViewer sviewer; 703 704 PetscFunctionBegin; 705 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&isascii);CHKERRQ(ierr); 706 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_DRAW_VIEWER,&isdraw);CHKERRQ(ierr); 707 if (isascii) { 708 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 709 if (format == PETSC_VIEWER_FORMAT_ASCII_INFO_LONG) { 710 MatInfo info; 711 ierr = MPI_Comm_rank(mat->comm,&rank);CHKERRQ(ierr); 712 ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr); 713 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %d nz %d nz alloced %d bs %d mem %d\n", 714 rank,mat->m,(int)info.nz_used*bs,(int)info.nz_allocated*bs, 715 baij->bs,(int)info.memory);CHKERRQ(ierr); 716 ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr); 717 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %d \n",rank,(int)info.nz_used*bs);CHKERRQ(ierr); 718 ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr); 719 ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %d \n",rank,(int)info.nz_used*bs);CHKERRQ(ierr); 720 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 721 ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr); 722 PetscFunctionReturn(0); 723 } else if (format == PETSC_VIEWER_FORMAT_ASCII_INFO) { 724 ierr = PetscViewerASCIIPrintf(viewer," block size is %d\n",bs);CHKERRQ(ierr); 725 PetscFunctionReturn(0); 726 } 727 } 728 729 if (isdraw) { 730 PetscDraw draw; 731 PetscTruth isnull; 732 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 733 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); 734 } 735 736 if (size == 1) { 737 ierr = MatView(baij->A,viewer);CHKERRQ(ierr); 738 } else { 739 /* assemble the entire matrix onto first processor. */ 740 Mat A; 741 Mat_SeqSBAIJ *Aloc; 742 Mat_SeqBAIJ *Bloc; 743 int M = mat->M,N = mat->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs; 744 MatScalar *a; 745 746 if (!rank) { 747 ierr = MatCreateMPISBAIJ(mat->comm,baij->bs,M,N,M,N,0,PETSC_NULL,0,PETSC_NULL,&A);CHKERRQ(ierr); 748 } else { 749 ierr = MatCreateMPISBAIJ(mat->comm,baij->bs,0,0,M,N,0,PETSC_NULL,0,PETSC_NULL,&A);CHKERRQ(ierr); 750 } 751 PetscLogObjectParent(mat,A); 752 753 /* copy over the A part */ 754 Aloc = (Mat_SeqSBAIJ*)baij->A->data; 755 ai = Aloc->i; aj = Aloc->j; a = Aloc->a; 756 ierr = PetscMalloc(bs*sizeof(int),&( rvals ));CHKERRQ(ierr); 757 758 for (i=0; i<mbs; i++) { 759 rvals[0] = bs*(baij->rstart + i); 760 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 761 for (j=ai[i]; j<ai[i+1]; j++) { 762 col = (baij->cstart+aj[j])*bs; 763 for (k=0; k<bs; k++) { 764 ierr = MatSetValues_MPISBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 765 col++; a += bs; 766 } 767 } 768 } 769 /* copy over the B part */ 770 Bloc = (Mat_SeqBAIJ*)baij->B->data; 771 ai = Bloc->i; aj = Bloc->j; a = Bloc->a; 772 for (i=0; i<mbs; i++) { 773 rvals[0] = bs*(baij->rstart + i); 774 for (j=1; j<bs; j++) { rvals[j] = rvals[j-1] + 1; } 775 for (j=ai[i]; j<ai[i+1]; j++) { 776 col = baij->garray[aj[j]]*bs; 777 for (k=0; k<bs; k++) { 778 ierr = MatSetValues_MPISBAIJ_MatScalar(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr); 779 col++; a += bs; 780 } 781 } 782 } 783 ierr = PetscFree(rvals);CHKERRQ(ierr); 784 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 785 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 786 /* 787 Everyone has to call to draw the matrix since the graphics waits are 788 synchronized across all processors that share the PetscDraw object 789 */ 790 ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr); 791 if (!rank) { 792 ierr = MatView(((Mat_MPISBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr); 793 } 794 ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr); 795 ierr = MatDestroy(A);CHKERRQ(ierr); 796 } 797 PetscFunctionReturn(0); 798 } 799 800 #undef __FUNC__ 801 #define __FUNC__ "MatView_MPISBAIJ" 802 int MatView_MPISBAIJ(Mat mat,PetscViewer viewer) 803 { 804 int ierr; 805 PetscTruth isascii,isdraw,issocket,isbinary; 806 807 PetscFunctionBegin; 808 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&isascii);CHKERRQ(ierr); 809 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_DRAW_VIEWER,&isdraw);CHKERRQ(ierr); 810 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_SOCKET,&issocket);CHKERRQ(ierr); 811 ierr = PetscTypeCompare((PetscObject)viewer,PETSC_BINARY_VIEWER,&isbinary);CHKERRQ(ierr); 812 if (isascii || isdraw || issocket || isbinary) { 813 ierr = MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr); 814 } else { 815 SETERRQ1(1,"Viewer type %s not supported by MPISBAIJ matrices",((PetscObject)viewer)->type_name); 816 } 817 PetscFunctionReturn(0); 818 } 819 820 #undef __FUNC__ 821 #define __FUNC__ "MatDestroy_MPISBAIJ" 822 int MatDestroy_MPISBAIJ(Mat mat) 823 { 824 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 825 int ierr; 826 827 PetscFunctionBegin; 828 #if defined(PETSC_USE_LOG) 829 PetscLogObjectState((PetscObject)mat,"Rows=%d,Cols=%d",mat->M,mat->N); 830 #endif 831 ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr); 832 ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr); 833 ierr = PetscFree(baij->rowners);CHKERRQ(ierr); 834 ierr = MatDestroy(baij->A);CHKERRQ(ierr); 835 ierr = MatDestroy(baij->B);CHKERRQ(ierr); 836 #if defined (PETSC_USE_CTABLE) 837 if (baij->colmap) {ierr = PetscTableDelete(baij->colmap);CHKERRQ(ierr);} 838 #else 839 if (baij->colmap) {ierr = PetscFree(baij->colmap);CHKERRQ(ierr);} 840 #endif 841 if (baij->garray) {ierr = PetscFree(baij->garray);CHKERRQ(ierr);} 842 if (baij->lvec) {ierr = VecDestroy(baij->lvec);CHKERRQ(ierr);} 843 if (baij->Mvctx) {ierr = VecScatterDestroy(baij->Mvctx);CHKERRQ(ierr);} 844 if (baij->rowvalues) {ierr = PetscFree(baij->rowvalues);CHKERRQ(ierr);} 845 if (baij->barray) {ierr = PetscFree(baij->barray);CHKERRQ(ierr);} 846 if (baij->hd) {ierr = PetscFree(baij->hd);CHKERRQ(ierr);} 847 #if defined(PETSC_USE_MAT_SINGLE) 848 if (baij->setvaluescopy) {ierr = PetscFree(baij->setvaluescopy);CHKERRQ(ierr);} 849 #endif 850 ierr = PetscFree(baij);CHKERRQ(ierr); 851 PetscFunctionReturn(0); 852 } 853 854 #undef __FUNC__ 855 #define __FUNC__ "MatMult_MPISBAIJ" 856 int MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy) 857 { 858 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 859 int ierr,nt; 860 861 PetscFunctionBegin; 862 ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr); 863 if (nt != A->n) { 864 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx"); 865 } 866 ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr); 867 if (nt != A->m) { 868 SETERRQ(PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy"); 869 } 870 871 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 872 /* do diagonal part */ 873 ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr); 874 /* do supperdiagonal part */ 875 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 876 ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr); 877 /* do subdiagonal part */ 878 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 879 ierr = VecScatterBegin(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 880 ierr = VecScatterEnd(a->lvec,yy,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 881 882 PetscFunctionReturn(0); 883 } 884 885 #undef __FUNC__ 886 #define __FUNC__ "MatMultAdd_MPISBAIJ" 887 int MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 888 { 889 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 890 int ierr; 891 892 PetscFunctionBegin; 893 ierr = VecScatterBegin(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 894 /* do diagonal part */ 895 ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr); 896 /* do supperdiagonal part */ 897 ierr = VecScatterEnd(xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD,a->Mvctx);CHKERRQ(ierr); 898 ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr); 899 900 /* do subdiagonal part */ 901 ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr); 902 ierr = VecScatterBegin(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 903 ierr = VecScatterEnd(a->lvec,zz,ADD_VALUES,SCATTER_REVERSE,a->Mvctx);CHKERRQ(ierr); 904 905 PetscFunctionReturn(0); 906 } 907 908 #undef __FUNC__ 909 #define __FUNC__ "MatMultTranspose_MPISBAIJ" 910 int MatMultTranspose_MPISBAIJ(Mat A,Vec xx,Vec yy) 911 { 912 PetscFunctionBegin; 913 SETERRQ(1,"Matrix is symmetric. Call MatMult()."); 914 /* PetscFunctionReturn(0); */ 915 } 916 917 #undef __FUNC__ 918 #define __FUNC__ "MatMultTransposeAdd_MPISBAIJ" 919 int MatMultTransposeAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz) 920 { 921 PetscFunctionBegin; 922 SETERRQ(1,"Matrix is symmetric. Call MatMultAdd()."); 923 /* PetscFunctionReturn(0); */ 924 } 925 926 /* 927 This only works correctly for square matrices where the subblock A->A is the 928 diagonal block 929 */ 930 #undef __FUNC__ 931 #define __FUNC__ "MatGetDiagonal_MPISBAIJ" 932 int MatGetDiagonal_MPISBAIJ(Mat A,Vec v) 933 { 934 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 935 int ierr; 936 937 PetscFunctionBegin; 938 /* if (a->M != a->N) SETERRQ(PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */ 939 ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr); 940 PetscFunctionReturn(0); 941 } 942 943 #undef __FUNC__ 944 #define __FUNC__ "MatScale_MPISBAIJ" 945 int MatScale_MPISBAIJ(Scalar *aa,Mat A) 946 { 947 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 948 int ierr; 949 950 PetscFunctionBegin; 951 ierr = MatScale(aa,a->A);CHKERRQ(ierr); 952 ierr = MatScale(aa,a->B);CHKERRQ(ierr); 953 PetscFunctionReturn(0); 954 } 955 956 #undef __FUNC__ 957 #define __FUNC__ "MatGetOwnershipRange_MPISBAIJ" 958 int MatGetOwnershipRange_MPISBAIJ(Mat matin,int *m,int *n) 959 { 960 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 961 962 PetscFunctionBegin; 963 if (m) *m = mat->rstart*mat->bs; 964 if (n) *n = mat->rend*mat->bs; 965 PetscFunctionReturn(0); 966 } 967 968 #undef __FUNC__ 969 #define __FUNC__ "MatGetRow_MPISBAIJ" 970 int MatGetRow_MPISBAIJ(Mat matin,int row,int *nz,int **idx,Scalar **v) 971 { 972 Mat_MPISBAIJ *mat = (Mat_MPISBAIJ*)matin->data; 973 Scalar *vworkA,*vworkB,**pvA,**pvB,*v_p; 974 int bs = mat->bs,bs2 = mat->bs2,i,ierr,*cworkA,*cworkB,**pcA,**pcB; 975 int nztot,nzA,nzB,lrow,brstart = mat->rstart*bs,brend = mat->rend*bs; 976 int *cmap,*idx_p,cstart = mat->cstart; 977 978 PetscFunctionBegin; 979 if (mat->getrowactive == PETSC_TRUE) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Already active"); 980 mat->getrowactive = PETSC_TRUE; 981 982 if (!mat->rowvalues && (idx || v)) { 983 /* 984 allocate enough space to hold information from the longest row. 985 */ 986 Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data; 987 Mat_SeqBAIJ *Ba = (Mat_SeqBAIJ*)mat->B->data; 988 int max = 1,mbs = mat->mbs,tmp; 989 for (i=0; i<mbs; i++) { 990 tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */ 991 if (max < tmp) { max = tmp; } 992 } 993 ierr = PetscMalloc(max*bs2*(sizeof(int)+sizeof(Scalar)),& mat->rowvalues );CHKERRQ(ierr); 994 mat->rowindices = (int*)(mat->rowvalues + max*bs2); 995 } 996 997 if (row < brstart || row >= brend) SETERRQ(PETSC_ERR_SUP,"Only local rows") 998 lrow = row - brstart; /* local row index */ 999 1000 pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB; 1001 if (!v) {pvA = 0; pvB = 0;} 1002 if (!idx) {pcA = 0; if (!v) pcB = 0;} 1003 ierr = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1004 ierr = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1005 nztot = nzA + nzB; 1006 1007 cmap = mat->garray; 1008 if (v || idx) { 1009 if (nztot) { 1010 /* Sort by increasing column numbers, assuming A and B already sorted */ 1011 int imark = -1; 1012 if (v) { 1013 *v = v_p = mat->rowvalues; 1014 for (i=0; i<nzB; i++) { 1015 if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i]; 1016 else break; 1017 } 1018 imark = i; 1019 for (i=0; i<nzA; i++) v_p[imark+i] = vworkA[i]; 1020 for (i=imark; i<nzB; i++) v_p[nzA+i] = vworkB[i]; 1021 } 1022 if (idx) { 1023 *idx = idx_p = mat->rowindices; 1024 if (imark > -1) { 1025 for (i=0; i<imark; i++) { 1026 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs; 1027 } 1028 } else { 1029 for (i=0; i<nzB; i++) { 1030 if (cmap[cworkB[i]/bs] < cstart) 1031 idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1032 else break; 1033 } 1034 imark = i; 1035 } 1036 for (i=0; i<nzA; i++) idx_p[imark+i] = cstart*bs + cworkA[i]; 1037 for (i=imark; i<nzB; i++) idx_p[nzA+i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ; 1038 } 1039 } else { 1040 if (idx) *idx = 0; 1041 if (v) *v = 0; 1042 } 1043 } 1044 *nz = nztot; 1045 ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr); 1046 ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr); 1047 PetscFunctionReturn(0); 1048 } 1049 1050 #undef __FUNC__ 1051 #define __FUNC__ "MatRestoreRow_MPISBAIJ" 1052 int MatRestoreRow_MPISBAIJ(Mat mat,int row,int *nz,int **idx,Scalar **v) 1053 { 1054 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1055 1056 PetscFunctionBegin; 1057 if (baij->getrowactive == PETSC_FALSE) { 1058 SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called"); 1059 } 1060 baij->getrowactive = PETSC_FALSE; 1061 PetscFunctionReturn(0); 1062 } 1063 1064 #undef __FUNC__ 1065 #define __FUNC__ "MatGetBlockSize_MPISBAIJ" 1066 int MatGetBlockSize_MPISBAIJ(Mat mat,int *bs) 1067 { 1068 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1069 1070 PetscFunctionBegin; 1071 *bs = baij->bs; 1072 PetscFunctionReturn(0); 1073 } 1074 1075 #undef __FUNC__ 1076 #define __FUNC__ "MatZeroEntries_MPISBAIJ" 1077 int MatZeroEntries_MPISBAIJ(Mat A) 1078 { 1079 Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data; 1080 int ierr; 1081 1082 PetscFunctionBegin; 1083 ierr = MatZeroEntries(l->A);CHKERRQ(ierr); 1084 ierr = MatZeroEntries(l->B);CHKERRQ(ierr); 1085 PetscFunctionReturn(0); 1086 } 1087 1088 #undef __FUNC__ 1089 #define __FUNC__ "MatGetInfo_MPISBAIJ" 1090 int MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info) 1091 { 1092 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)matin->data; 1093 Mat A = a->A,B = a->B; 1094 int ierr; 1095 PetscReal isend[5],irecv[5]; 1096 1097 PetscFunctionBegin; 1098 info->block_size = (double)a->bs; 1099 ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr); 1100 isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded; 1101 isend[3] = info->memory; isend[4] = info->mallocs; 1102 ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr); 1103 isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded; 1104 isend[3] += info->memory; isend[4] += info->mallocs; 1105 if (flag == MAT_LOCAL) { 1106 info->nz_used = isend[0]; 1107 info->nz_allocated = isend[1]; 1108 info->nz_unneeded = isend[2]; 1109 info->memory = isend[3]; 1110 info->mallocs = isend[4]; 1111 } else if (flag == MAT_GLOBAL_MAX) { 1112 ierr = MPI_Allreduce(isend,irecv,5,MPI_DOUBLE,MPI_MAX,matin->comm);CHKERRQ(ierr); 1113 info->nz_used = irecv[0]; 1114 info->nz_allocated = irecv[1]; 1115 info->nz_unneeded = irecv[2]; 1116 info->memory = irecv[3]; 1117 info->mallocs = irecv[4]; 1118 } else if (flag == MAT_GLOBAL_SUM) { 1119 ierr = MPI_Allreduce(isend,irecv,5,MPI_DOUBLE,MPI_SUM,matin->comm);CHKERRQ(ierr); 1120 info->nz_used = irecv[0]; 1121 info->nz_allocated = irecv[1]; 1122 info->nz_unneeded = irecv[2]; 1123 info->memory = irecv[3]; 1124 info->mallocs = irecv[4]; 1125 } else { 1126 SETERRQ1(1,"Unknown MatInfoType argument %d",flag); 1127 } 1128 info->rows_global = (double)A->M; 1129 info->columns_global = (double)A->N; 1130 info->rows_local = (double)A->m; 1131 info->columns_local = (double)A->N; 1132 info->fill_ratio_given = 0; /* no parallel LU/ILU/Cholesky */ 1133 info->fill_ratio_needed = 0; 1134 info->factor_mallocs = 0; 1135 PetscFunctionReturn(0); 1136 } 1137 1138 #undef __FUNC__ 1139 #define __FUNC__ "MatSetOption_MPISBAIJ" 1140 int MatSetOption_MPISBAIJ(Mat A,MatOption op) 1141 { 1142 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1143 int ierr; 1144 1145 PetscFunctionBegin; 1146 if (op == MAT_NO_NEW_NONZERO_LOCATIONS || 1147 op == MAT_YES_NEW_NONZERO_LOCATIONS || 1148 op == MAT_COLUMNS_UNSORTED || 1149 op == MAT_COLUMNS_SORTED || 1150 op == MAT_NEW_NONZERO_ALLOCATION_ERR || 1151 op == MAT_KEEP_ZEROED_ROWS || 1152 op == MAT_NEW_NONZERO_LOCATION_ERR) { 1153 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1154 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1155 } else if (op == MAT_ROW_ORIENTED) { 1156 a->roworiented = PETSC_TRUE; 1157 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1158 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1159 } else if (op == MAT_ROWS_SORTED || 1160 op == MAT_ROWS_UNSORTED || 1161 op == MAT_SYMMETRIC || 1162 op == MAT_STRUCTURALLY_SYMMETRIC || 1163 op == MAT_YES_NEW_DIAGONALS || 1164 op == MAT_USE_HASH_TABLE) { 1165 PetscLogInfo(A,"Info:MatSetOption_MPIBAIJ:Option ignored\n"); 1166 } else if (op == MAT_COLUMN_ORIENTED) { 1167 a->roworiented = PETSC_FALSE; 1168 ierr = MatSetOption(a->A,op);CHKERRQ(ierr); 1169 ierr = MatSetOption(a->B,op);CHKERRQ(ierr); 1170 } else if (op == MAT_IGNORE_OFF_PROC_ENTRIES) { 1171 a->donotstash = PETSC_TRUE; 1172 } else if (op == MAT_NO_NEW_DIAGONALS) { 1173 SETERRQ(PETSC_ERR_SUP,"MAT_NO_NEW_DIAGONALS"); 1174 } else if (op == MAT_USE_HASH_TABLE) { 1175 a->ht_flag = PETSC_TRUE; 1176 } else { 1177 SETERRQ(PETSC_ERR_SUP,"unknown option"); 1178 } 1179 PetscFunctionReturn(0); 1180 } 1181 1182 #undef __FUNC__ 1183 #define __FUNC__ "MatTranspose_MPISBAIJ(" 1184 int MatTranspose_MPISBAIJ(Mat A,Mat *matout) 1185 { 1186 PetscFunctionBegin; 1187 SETERRQ(1,"Matrix is symmetric. MatTranspose() should not be called"); 1188 /* PetscFunctionReturn(0); */ 1189 } 1190 1191 #undef __FUNC__ 1192 #define __FUNC__ "MatDiagonalScale_MPISBAIJ" 1193 int MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr) 1194 { 1195 Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data; 1196 Mat a = baij->A,b = baij->B; 1197 int ierr,s1,s2,s3; 1198 1199 PetscFunctionBegin; 1200 if (ll != rr) { 1201 SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n"); 1202 } 1203 ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr); 1204 if (rr) { 1205 ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr); 1206 if (s1!=s3) SETERRQ(PETSC_ERR_ARG_SIZ,"right vector non-conforming local size"); 1207 /* Overlap communication with computation. */ 1208 ierr = VecScatterBegin(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1209 /*} if (ll) { */ 1210 ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr); 1211 if (s1!=s2) SETERRQ(PETSC_ERR_ARG_SIZ,"left vector non-conforming local size"); 1212 ierr = (*b->ops->diagonalscale)(b,ll,PETSC_NULL);CHKERRQ(ierr); 1213 /* } */ 1214 /* scale the diagonal block */ 1215 ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr); 1216 1217 /* if (rr) { */ 1218 /* Do a scatter end and then right scale the off-diagonal block */ 1219 ierr = VecScatterEnd(rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD,baij->Mvctx);CHKERRQ(ierr); 1220 ierr = (*b->ops->diagonalscale)(b,PETSC_NULL,baij->lvec);CHKERRQ(ierr); 1221 } 1222 1223 PetscFunctionReturn(0); 1224 } 1225 1226 #undef __FUNC__ 1227 #define __FUNC__ "MatZeroRows_MPISBAIJ" 1228 int MatZeroRows_MPISBAIJ(Mat A,IS is,Scalar *diag) 1229 { 1230 Mat_MPISBAIJ *l = (Mat_MPISBAIJ*)A->data; 1231 int i,ierr,N,*rows,*owners = l->rowners,size = l->size; 1232 int *procs,*nprocs,j,idx,nsends,*work,row; 1233 int nmax,*svalues,*starts,*owner,nrecvs,rank = l->rank; 1234 int *rvalues,tag = A->tag,count,base,slen,n,*source; 1235 int *lens,imdex,*lrows,*values,bs=l->bs,rstart_bs=l->rstart_bs; 1236 MPI_Comm comm = A->comm; 1237 MPI_Request *send_waits,*recv_waits; 1238 MPI_Status recv_status,*send_status; 1239 IS istmp; 1240 PetscTruth found; 1241 1242 PetscFunctionBegin; 1243 ierr = ISGetSize(is,&N);CHKERRQ(ierr); 1244 ierr = ISGetIndices(is,&rows);CHKERRQ(ierr); 1245 1246 /* first count number of contributors to each processor */ 1247 ierr = PetscMalloc(2*size*sizeof(int),&( nprocs ));CHKERRQ(ierr); 1248 ierr = PetscMemzero(nprocs,2*size*sizeof(int));CHKERRQ(ierr); 1249 procs = nprocs + size; 1250 ierr = PetscMalloc((N+1)*sizeof(int),& owner );CHKERRQ(ierr); /* see note*/ 1251 for (i=0; i<N; i++) { 1252 idx = rows[i]; 1253 found = PETSC_FALSE; 1254 for (j=0; j<size; j++) { 1255 if (idx >= owners[j]*bs && idx < owners[j+1]*bs) { 1256 nprocs[j]++; procs[j] = 1; owner[i] = j; found = PETSC_TRUE; break; 1257 } 1258 } 1259 if (!found) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Index out of range"); 1260 } 1261 nsends = 0; for (i=0; i<size; i++) { nsends += procs[i];} 1262 1263 /* inform other processors of number of messages and max length*/ 1264 ierr = PetscMalloc(2*size*sizeof(int),&( work ));CHKERRQ(ierr); 1265 ierr = MPI_Allreduce(nprocs,work,2*size,MPI_INT,PetscMaxSum_Op,comm);CHKERRQ(ierr); 1266 nmax = work[rank]; 1267 nrecvs = work[size+rank]; 1268 ierr = PetscFree(work);CHKERRQ(ierr); 1269 1270 /* post receives: */ 1271 ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(int),& rvalues );CHKERRQ(ierr); 1272 ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),& recv_waits );CHKERRQ(ierr); 1273 for (i=0; i<nrecvs; i++) { 1274 ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPI_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr); 1275 } 1276 1277 /* do sends: 1278 1) starts[i] gives the starting index in svalues for stuff going to 1279 the ith processor 1280 */ 1281 ierr = PetscMalloc((N+1)*sizeof(int),& svalues );CHKERRQ(ierr); 1282 ierr = PetscMalloc((nsends+1)*sizeof(MPI_Request),& send_waits );CHKERRQ(ierr); 1283 ierr = PetscMalloc((size+1)*sizeof(int),& starts );CHKERRQ(ierr); 1284 starts[0] = 0; 1285 for (i=1; i<size; i++) { starts[i] = starts[i-1] + nprocs[i-1];} 1286 for (i=0; i<N; i++) { 1287 svalues[starts[owner[i]]++] = rows[i]; 1288 } 1289 ierr = ISRestoreIndices(is,&rows);CHKERRQ(ierr); 1290 1291 starts[0] = 0; 1292 for (i=1; i<size+1; i++) { starts[i] = starts[i-1] + nprocs[i-1];} 1293 count = 0; 1294 for (i=0; i<size; i++) { 1295 if (procs[i]) { 1296 ierr = MPI_Isend(svalues+starts[i],nprocs[i],MPI_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr); 1297 } 1298 } 1299 ierr = PetscFree(starts);CHKERRQ(ierr); 1300 1301 base = owners[rank]*bs; 1302 1303 /* wait on receives */ 1304 ierr = PetscMalloc(2*(nrecvs+1)*sizeof(int),& lens );CHKERRQ(ierr); 1305 source = lens + nrecvs; 1306 count = nrecvs; slen = 0; 1307 while (count) { 1308 ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr); 1309 /* unpack receives into our local space */ 1310 ierr = MPI_Get_count(&recv_status,MPI_INT,&n);CHKERRQ(ierr); 1311 source[imdex] = recv_status.MPI_SOURCE; 1312 lens[imdex] = n; 1313 slen += n; 1314 count--; 1315 } 1316 ierr = PetscFree(recv_waits);CHKERRQ(ierr); 1317 1318 /* move the data into the send scatter */ 1319 ierr = PetscMalloc((slen+1)*sizeof(int),& lrows );CHKERRQ(ierr); 1320 count = 0; 1321 for (i=0; i<nrecvs; i++) { 1322 values = rvalues + i*nmax; 1323 for (j=0; j<lens[i]; j++) { 1324 lrows[count++] = values[j] - base; 1325 } 1326 } 1327 ierr = PetscFree(rvalues);CHKERRQ(ierr); 1328 ierr = PetscFree(lens);CHKERRQ(ierr); 1329 ierr = PetscFree(owner);CHKERRQ(ierr); 1330 ierr = PetscFree(nprocs);CHKERRQ(ierr); 1331 1332 /* actually zap the local rows */ 1333 ierr = ISCreateGeneral(PETSC_COMM_SELF,slen,lrows,&istmp);CHKERRQ(ierr); 1334 PetscLogObjectParent(A,istmp); 1335 1336 /* 1337 Zero the required rows. If the "diagonal block" of the matrix 1338 is square and the user wishes to set the diagonal we use seperate 1339 code so that MatSetValues() is not called for each diagonal allocating 1340 new memory, thus calling lots of mallocs and slowing things down. 1341 1342 Contributed by: Mathew Knepley 1343 */ 1344 /* must zero l->B before l->A because the (diag) case below may put values into l->B*/ 1345 ierr = MatZeroRows_SeqBAIJ(l->B,istmp,0);CHKERRQ(ierr); 1346 if (diag && (l->A->M == l->A->N)) { 1347 ierr = MatZeroRows_SeqSBAIJ(l->A,istmp,diag);CHKERRQ(ierr); 1348 } else if (diag) { 1349 ierr = MatZeroRows_SeqSBAIJ(l->A,istmp,0);CHKERRQ(ierr); 1350 if (((Mat_SeqSBAIJ*)l->A->data)->nonew) { 1351 SETERRQ(PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options \n\ 1352 MAT_NO_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR"); 1353 } 1354 for (i=0; i<slen; i++) { 1355 row = lrows[i] + rstart_bs; 1356 ierr = MatSetValues(A,1,&row,1,&row,diag,INSERT_VALUES);CHKERRQ(ierr); 1357 } 1358 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1359 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1360 } else { 1361 ierr = MatZeroRows_SeqSBAIJ(l->A,istmp,0);CHKERRQ(ierr); 1362 } 1363 1364 ierr = ISDestroy(istmp);CHKERRQ(ierr); 1365 ierr = PetscFree(lrows);CHKERRQ(ierr); 1366 1367 /* wait on sends */ 1368 if (nsends) { 1369 ierr = PetscMalloc(nsends*sizeof(MPI_Status),&( send_status ));CHKERRQ(ierr); 1370 ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr); 1371 ierr = PetscFree(send_status);CHKERRQ(ierr); 1372 } 1373 ierr = PetscFree(send_waits);CHKERRQ(ierr); 1374 ierr = PetscFree(svalues);CHKERRQ(ierr); 1375 1376 PetscFunctionReturn(0); 1377 } 1378 1379 #undef __FUNC__ 1380 #define __FUNC__ "MatPrintHelp_MPISBAIJ" 1381 int MatPrintHelp_MPISBAIJ(Mat A) 1382 { 1383 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1384 MPI_Comm comm = A->comm; 1385 static int called = 0; 1386 int ierr; 1387 1388 PetscFunctionBegin; 1389 if (!a->rank) { 1390 ierr = MatPrintHelp_SeqSBAIJ(a->A);CHKERRQ(ierr); 1391 } 1392 if (called) {PetscFunctionReturn(0);} else called = 1; 1393 ierr = (*PetscHelpPrintf)(comm," Options for MATMPISBAIJ matrix format (the defaults):\n");CHKERRQ(ierr); 1394 ierr = (*PetscHelpPrintf)(comm," -mat_use_hash_table <factor>: Use hashtable for efficient matrix assembly\n");CHKERRQ(ierr); 1395 PetscFunctionReturn(0); 1396 } 1397 1398 #undef __FUNC__ 1399 #define __FUNC__ "MatSetUnfactored_MPISBAIJ" 1400 int MatSetUnfactored_MPISBAIJ(Mat A) 1401 { 1402 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 1403 int ierr; 1404 1405 PetscFunctionBegin; 1406 ierr = MatSetUnfactored(a->A);CHKERRQ(ierr); 1407 PetscFunctionReturn(0); 1408 } 1409 1410 static int MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat *); 1411 1412 #undef __FUNC__ 1413 #define __FUNC__ "MatEqual_MPISBAIJ" 1414 int MatEqual_MPISBAIJ(Mat A,Mat B,PetscTruth *flag) 1415 { 1416 Mat_MPISBAIJ *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data; 1417 Mat a,b,c,d; 1418 PetscTruth flg; 1419 int ierr; 1420 1421 PetscFunctionBegin; 1422 ierr = PetscTypeCompare((PetscObject)B,MATMPISBAIJ,&flg);CHKERRQ(ierr); 1423 if (!flg) SETERRQ(PETSC_ERR_ARG_INCOMP,"Matrices must be same type"); 1424 a = matA->A; b = matA->B; 1425 c = matB->A; d = matB->B; 1426 1427 ierr = MatEqual(a,c,&flg);CHKERRQ(ierr); 1428 if (flg == PETSC_TRUE) { 1429 ierr = MatEqual(b,d,&flg);CHKERRQ(ierr); 1430 } 1431 ierr = MPI_Allreduce(&flg,flag,1,MPI_INT,MPI_LAND,A->comm);CHKERRQ(ierr); 1432 PetscFunctionReturn(0); 1433 } 1434 1435 #undef __FUNC__ 1436 #define __FUNC__ "MatSetUpPreallocation_MPISBAIJ" 1437 int MatSetUpPreallocation_MPISBAIJ(Mat A) 1438 { 1439 int ierr; 1440 1441 PetscFunctionBegin; 1442 ierr = MatMPISBAIJSetPreallocation(A,1,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr); 1443 PetscFunctionReturn(0); 1444 } 1445 /* -------------------------------------------------------------------*/ 1446 static struct _MatOps MatOps_Values = { 1447 MatSetValues_MPISBAIJ, 1448 MatGetRow_MPISBAIJ, 1449 MatRestoreRow_MPISBAIJ, 1450 MatMult_MPISBAIJ, 1451 MatMultAdd_MPISBAIJ, 1452 MatMultTranspose_MPISBAIJ, 1453 MatMultTransposeAdd_MPISBAIJ, 1454 0, 1455 0, 1456 0, 1457 0, 1458 0, 1459 0, 1460 0, 1461 MatTranspose_MPISBAIJ, 1462 MatGetInfo_MPISBAIJ, 1463 MatEqual_MPISBAIJ, 1464 MatGetDiagonal_MPISBAIJ, 1465 MatDiagonalScale_MPISBAIJ, 1466 MatNorm_MPISBAIJ, 1467 MatAssemblyBegin_MPISBAIJ, 1468 MatAssemblyEnd_MPISBAIJ, 1469 0, 1470 MatSetOption_MPISBAIJ, 1471 MatZeroEntries_MPISBAIJ, 1472 MatZeroRows_MPISBAIJ, 1473 0, 1474 0, 1475 0, 1476 0, 1477 MatSetUpPreallocation_MPISBAIJ, 1478 0, 1479 MatGetOwnershipRange_MPISBAIJ, 1480 0, 1481 0, 1482 0, 1483 0, 1484 MatDuplicate_MPISBAIJ, 1485 0, 1486 0, 1487 0, 1488 0, 1489 0, 1490 MatGetSubMatrices_MPISBAIJ, 1491 MatIncreaseOverlap_MPISBAIJ, 1492 MatGetValues_MPISBAIJ, 1493 0, 1494 MatPrintHelp_MPISBAIJ, 1495 MatScale_MPISBAIJ, 1496 0, 1497 0, 1498 0, 1499 MatGetBlockSize_MPISBAIJ, 1500 0, 1501 0, 1502 0, 1503 0, 1504 0, 1505 0, 1506 MatSetUnfactored_MPISBAIJ, 1507 0, 1508 MatSetValuesBlocked_MPISBAIJ, 1509 0, 1510 0, 1511 0, 1512 MatGetMaps_Petsc, 1513 0, 1514 0, 1515 0, 1516 0, 1517 0, 1518 0, 1519 MatGetRowMax_MPISBAIJ}; 1520 1521 1522 EXTERN_C_BEGIN 1523 #undef __FUNC__ 1524 #define __FUNC__ "MatGetDiagonalBlock_MPISBAIJ" 1525 int MatGetDiagonalBlock_MPISBAIJ(Mat A,PetscTruth *iscopy,MatReuse reuse,Mat *a) 1526 { 1527 PetscFunctionBegin; 1528 *a = ((Mat_MPISBAIJ *)A->data)->A; 1529 *iscopy = PETSC_FALSE; 1530 PetscFunctionReturn(0); 1531 } 1532 EXTERN_C_END 1533 1534 EXTERN_C_BEGIN 1535 #undef __FUNC__ 1536 #define __FUNC__ "MatCreate_MPISBAIJ" 1537 int MatCreate_MPISBAIJ(Mat B) 1538 { 1539 Mat_MPISBAIJ *b; 1540 int ierr; 1541 PetscTruth flg; 1542 1543 PetscFunctionBegin; 1544 1545 ierr = PetscNew(Mat_MPISBAIJ,&b);CHKERRQ(ierr); 1546 B->data = (void*)b; 1547 ierr = PetscMemzero(b,sizeof(Mat_MPISBAIJ));CHKERRQ(ierr); 1548 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 1549 1550 B->ops->destroy = MatDestroy_MPISBAIJ; 1551 B->ops->view = MatView_MPISBAIJ; 1552 B->mapping = 0; 1553 B->factor = 0; 1554 B->assembled = PETSC_FALSE; 1555 1556 B->insertmode = NOT_SET_VALUES; 1557 ierr = MPI_Comm_rank(B->comm,&b->rank);CHKERRQ(ierr); 1558 ierr = MPI_Comm_size(B->comm,&b->size);CHKERRQ(ierr); 1559 1560 /* build local table of row and column ownerships */ 1561 b->rowners = (int*)PetscMalloc(3*(b->size+2)*sizeof(int));CHKERRQ(ierr); 1562 b->cowners = b->rowners + b->size + 2; 1563 b->rowners_bs = b->cowners + b->size + 2; 1564 PetscLogObjectMemory(B,3*(b->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPISBAIJ)); 1565 1566 /* build cache for off array entries formed */ 1567 ierr = MatStashCreate_Private(B->comm,1,&B->stash);CHKERRQ(ierr); 1568 b->donotstash = PETSC_FALSE; 1569 b->colmap = PETSC_NULL; 1570 b->garray = PETSC_NULL; 1571 b->roworiented = PETSC_TRUE; 1572 1573 #if defined(PEYSC_USE_MAT_SINGLE) 1574 /* stuff for MatSetValues_XXX in single precision */ 1575 b->lensetvalues = 0; 1576 b->setvaluescopy = PETSC_NULL; 1577 #endif 1578 1579 /* stuff used in block assembly */ 1580 b->barray = 0; 1581 1582 /* stuff used for matrix vector multiply */ 1583 b->lvec = 0; 1584 b->Mvctx = 0; 1585 1586 /* stuff for MatGetRow() */ 1587 b->rowindices = 0; 1588 b->rowvalues = 0; 1589 b->getrowactive = PETSC_FALSE; 1590 1591 /* hash table stuff */ 1592 b->ht = 0; 1593 b->hd = 0; 1594 b->ht_size = 0; 1595 b->ht_flag = PETSC_FALSE; 1596 b->ht_fact = 0; 1597 b->ht_total_ct = 0; 1598 b->ht_insert_ct = 0; 1599 1600 ierr = PetscOptionsHasName(PETSC_NULL,"-mat_use_hash_table",&flg);CHKERRQ(ierr); 1601 if (flg) { 1602 double fact = 1.39; 1603 ierr = MatSetOption(B,MAT_USE_HASH_TABLE);CHKERRQ(ierr); 1604 ierr = PetscOptionsGetDouble(PETSC_NULL,"-mat_use_hash_table",&fact,PETSC_NULL);CHKERRQ(ierr); 1605 if (fact <= 1.0) fact = 1.39; 1606 ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr); 1607 PetscLogInfo(0,"MatCreateMPISBAIJ:Hash table Factor used %5.2f\n",fact); 1608 } 1609 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 1610 "MatStoreValues_MPISBAIJ", 1611 MatStoreValues_MPISBAIJ);CHKERRQ(ierr); 1612 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 1613 "MatRetrieveValues_MPISBAIJ", 1614 MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr); 1615 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetDiagonalBlock_C", 1616 "MatGetDiagonalBlock_MPISBAIJ", 1617 MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr); 1618 PetscFunctionReturn(0); 1619 } 1620 EXTERN_C_END 1621 1622 #undef __FUNC__ 1623 #define __FUNC__ "MatMPISBAIJSetPreallocation" 1624 /*@C 1625 MatMPISBAIJSetPreallocation - For good matrix assembly performance 1626 the user should preallocate the matrix storage by setting the parameters 1627 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1628 performance can be increased by more than a factor of 50. 1629 1630 Collective on Mat 1631 1632 Input Parameters: 1633 + A - the matrix 1634 . bs - size of blockk 1635 . d_nz - number of block nonzeros per block row in diagonal portion of local 1636 submatrix (same for all local rows) 1637 . d_nnz - array containing the number of block nonzeros in the various block rows 1638 of the in diagonal portion of the local (possibly different for each block 1639 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 1640 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1641 submatrix (same for all local rows). 1642 - o_nnz - array containing the number of nonzeros in the various block rows of the 1643 off-diagonal portion of the local submatrix (possibly different for 1644 each block row) or PETSC_NULL. 1645 1646 1647 Options Database Keys: 1648 . -mat_no_unroll - uses code that does not unroll the loops in the 1649 block calculations (much slower) 1650 . -mat_block_size - size of the blocks to use 1651 1652 Notes: 1653 1654 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1655 than it must be used on all processors that share the object for that argument. 1656 1657 Storage Information: 1658 For a square global matrix we define each processor's diagonal portion 1659 to be its local rows and the corresponding columns (a square submatrix); 1660 each processor's off-diagonal portion encompasses the remainder of the 1661 local matrix (a rectangular submatrix). 1662 1663 The user can specify preallocated storage for the diagonal part of 1664 the local submatrix with either d_nz or d_nnz (not both). Set 1665 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1666 memory allocation. Likewise, specify preallocated storage for the 1667 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1668 1669 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1670 the figure below we depict these three local rows and all columns (0-11). 1671 1672 .vb 1673 0 1 2 3 4 5 6 7 8 9 10 11 1674 ------------------- 1675 row 3 | o o o d d d o o o o o o 1676 row 4 | o o o d d d o o o o o o 1677 row 5 | o o o d d d o o o o o o 1678 ------------------- 1679 .ve 1680 1681 Thus, any entries in the d locations are stored in the d (diagonal) 1682 submatrix, and any entries in the o locations are stored in the 1683 o (off-diagonal) submatrix. Note that the d and the o submatrices are 1684 stored simply in the MATSEQBAIJ format for compressed row storage. 1685 1686 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 1687 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1688 In general, for PDE problems in which most nonzeros are near the diagonal, 1689 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1690 or you will get TERRIBLE performance; see the users' manual chapter on 1691 matrices. 1692 1693 Level: intermediate 1694 1695 .keywords: matrix, block, aij, compressed row, sparse, parallel 1696 1697 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1698 @*/ 1699 1700 int MatMPISBAIJSetPreallocation(Mat B,int bs,int d_nz,int *d_nnz,int o_nz,int *o_nnz) 1701 { 1702 Mat_MPISBAIJ *b; 1703 int ierr,i,mbs,Mbs=PETSC_DECIDE; 1704 PetscTruth flg2; 1705 1706 PetscFunctionBegin; 1707 ierr = PetscTypeCompare((PetscObject)B,MATMPISBAIJ,&flg2);CHKERRQ(ierr); 1708 if (!flg2) PetscFunctionReturn(0); 1709 1710 ierr = PetscOptionsGetInt(PETSC_NULL,"-mat_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 1711 1712 if (bs < 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive"); 1713 if (d_nz < -2) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"d_nz cannot be less than -2: value %d",d_nz); 1714 if (o_nz < -2) SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"o_nz cannot be less than -2: value %d",o_nz); 1715 if (d_nnz) { 1716 for (i=0; i<B->m/bs; i++) { 1717 if (d_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"d_nnz cannot be less than -1: local row %d value %d",i,d_nnz[i]); 1718 } 1719 } 1720 if (o_nnz) { 1721 for (i=0; i<B->m/bs; i++) { 1722 if (o_nnz[i] < 0) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,"o_nnz cannot be less than -1: local row %d value %d",i,o_nnz[i]); 1723 } 1724 } 1725 B->preallocated = PETSC_TRUE; 1726 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->m,&B->M);CHKERRQ(ierr); 1727 ierr = PetscSplitOwnershipBlock(B->comm,bs,&B->n,&B->N);CHKERRQ(ierr); 1728 ierr = MapCreateMPI(B->comm,B->m,B->M,&B->rmap);CHKERRQ(ierr); 1729 ierr = MapCreateMPI(B->comm,B->m,B->M,&B->cmap);CHKERRQ(ierr); 1730 1731 b = (Mat_MPISBAIJ*)B->data; 1732 mbs = B->m/bs; 1733 Mbs = B->M/bs; 1734 if (mbs*bs != B->m) { 1735 SETERRQ2(PETSC_ERR_ARG_SIZ,"No of local rows %d must be divisible by blocksize %d",B->m,bs); 1736 } 1737 1738 b->bs = bs; 1739 b->bs2 = bs*bs; 1740 b->mbs = mbs; 1741 b->nbs = mbs; 1742 b->Mbs = Mbs; 1743 b->Nbs = Mbs; 1744 1745 ierr = MPI_Allgather(&b->mbs,1,MPI_INT,b->rowners+1,1,MPI_INT,B->comm);CHKERRQ(ierr); 1746 b->rowners[0] = 0; 1747 for (i=2; i<=b->size; i++) { 1748 b->rowners[i] += b->rowners[i-1]; 1749 } 1750 b->rstart = b->rowners[b->rank]; 1751 b->rend = b->rowners[b->rank+1]; 1752 b->cstart = b->rstart; 1753 b->cend = b->rend; 1754 for (i=0; i<=b->size; i++) { 1755 b->rowners_bs[i] = b->rowners[i]*bs; 1756 } 1757 b->rstart_bs = b-> rstart*bs; 1758 b->rend_bs = b->rend*bs; 1759 1760 b->cstart_bs = b->cstart*bs; 1761 b->cend_bs = b->cend*bs; 1762 1763 1764 if (d_nz == PETSC_DEFAULT) d_nz = 5; 1765 ierr = MatCreateSeqSBAIJ(PETSC_COMM_SELF,bs,B->m,B->m,d_nz,d_nnz,&b->A);CHKERRQ(ierr); 1766 PetscLogObjectParent(B,b->A); 1767 if (o_nz == PETSC_DEFAULT) o_nz = 0; 1768 ierr = MatCreateSeqBAIJ(PETSC_COMM_SELF,bs,B->m,B->M,o_nz,o_nnz,&b->B);CHKERRQ(ierr); 1769 PetscLogObjectParent(B,b->B); 1770 1771 /* build cache for off array entries formed */ 1772 ierr = MatStashCreate_Private(B->comm,bs,&B->bstash);CHKERRQ(ierr); 1773 1774 PetscFunctionReturn(0); 1775 } 1776 1777 #undef __FUNC__ 1778 #define __FUNC__ "MatCreateMPISBAIJ" 1779 /*@C 1780 MatCreateMPISBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format 1781 (block compressed row). For good matrix assembly performance 1782 the user should preallocate the matrix storage by setting the parameters 1783 d_nz (or d_nnz) and o_nz (or o_nnz). By setting these parameters accurately, 1784 performance can be increased by more than a factor of 50. 1785 1786 Collective on MPI_Comm 1787 1788 Input Parameters: 1789 + comm - MPI communicator 1790 . bs - size of blockk 1791 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 1792 This value should be the same as the local size used in creating the 1793 y vector for the matrix-vector product y = Ax. 1794 . n - number of local columns (or PETSC_DECIDE to have calculated if N is given) 1795 This value should be the same as the local size used in creating the 1796 x vector for the matrix-vector product y = Ax. 1797 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 1798 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 1799 . d_nz - number of block nonzeros per block row in diagonal portion of local 1800 submatrix (same for all local rows) 1801 . d_nnz - array containing the number of block nonzeros in the various block rows 1802 of the in diagonal portion of the local (possibly different for each block 1803 row) or PETSC_NULL. You must leave room for the diagonal entry even if it is zero. 1804 . o_nz - number of block nonzeros per block row in the off-diagonal portion of local 1805 submatrix (same for all local rows). 1806 - o_nnz - array containing the number of nonzeros in the various block rows of the 1807 off-diagonal portion of the local submatrix (possibly different for 1808 each block row) or PETSC_NULL. 1809 1810 Output Parameter: 1811 . A - the matrix 1812 1813 Options Database Keys: 1814 . -mat_no_unroll - uses code that does not unroll the loops in the 1815 block calculations (much slower) 1816 . -mat_block_size - size of the blocks to use 1817 . -mat_mpi - use the parallel matrix data structures even on one processor 1818 (defaults to using SeqBAIJ format on one processor) 1819 1820 Notes: 1821 The user MUST specify either the local or global matrix dimensions 1822 (possibly both). 1823 1824 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one processor 1825 than it must be used on all processors that share the object for that argument. 1826 1827 Storage Information: 1828 For a square global matrix we define each processor's diagonal portion 1829 to be its local rows and the corresponding columns (a square submatrix); 1830 each processor's off-diagonal portion encompasses the remainder of the 1831 local matrix (a rectangular submatrix). 1832 1833 The user can specify preallocated storage for the diagonal part of 1834 the local submatrix with either d_nz or d_nnz (not both). Set 1835 d_nz=PETSC_DEFAULT and d_nnz=PETSC_NULL for PETSc to control dynamic 1836 memory allocation. Likewise, specify preallocated storage for the 1837 off-diagonal part of the local submatrix with o_nz or o_nnz (not both). 1838 1839 Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In 1840 the figure below we depict these three local rows and all columns (0-11). 1841 1842 .vb 1843 0 1 2 3 4 5 6 7 8 9 10 11 1844 ------------------- 1845 row 3 | o o o d d d o o o o o o 1846 row 4 | o o o d d d o o o o o o 1847 row 5 | o o o d d d o o o o o o 1848 ------------------- 1849 .ve 1850 1851 Thus, any entries in the d locations are stored in the d (diagonal) 1852 submatrix, and any entries in the o locations are stored in the 1853 o (off-diagonal) submatrix. Note that the d and the o submatrices are 1854 stored simply in the MATSEQBAIJ format for compressed row storage. 1855 1856 Now d_nz should indicate the number of block nonzeros per row in the d matrix, 1857 and o_nz should indicate the number of block nonzeros per row in the o matrix. 1858 In general, for PDE problems in which most nonzeros are near the diagonal, 1859 one expects d_nz >> o_nz. For large problems you MUST preallocate memory 1860 or you will get TERRIBLE performance; see the users' manual chapter on 1861 matrices. 1862 1863 Level: intermediate 1864 1865 .keywords: matrix, block, aij, compressed row, sparse, parallel 1866 1867 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateMPIBAIJ() 1868 @*/ 1869 1870 int MatCreateMPISBAIJ(MPI_Comm comm,int bs,int m,int n,int M,int N,int d_nz,int *d_nnz,int o_nz,int *o_nnz,Mat *A) 1871 { 1872 int ierr,size; 1873 1874 PetscFunctionBegin; 1875 ierr = MatCreate(comm,m,n,M,N,A);CHKERRQ(ierr); 1876 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1877 if (size > 1) { 1878 ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr); 1879 ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 1880 } else { 1881 ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr); 1882 ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr); 1883 } 1884 PetscFunctionReturn(0); 1885 } 1886 1887 1888 #undef __FUNC__ 1889 #define __FUNC__ "MatDuplicate_MPISBAIJ" 1890 static int MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat) 1891 { 1892 Mat mat; 1893 Mat_MPISBAIJ *a,*oldmat = (Mat_MPISBAIJ*)matin->data; 1894 int ierr,len=0; 1895 1896 PetscFunctionBegin; 1897 *newmat = 0; 1898 ierr = MatCreate(matin->comm,matin->m,matin->n,matin->M,matin->N,&mat);CHKERRQ(ierr); 1899 ierr = MatSetType(mat,MATMPISBAIJ);CHKERRQ(ierr); 1900 mat->preallocated = PETSC_TRUE; 1901 a = (Mat_MPISBAIJ*)mat->data; 1902 a->bs = oldmat->bs; 1903 a->bs2 = oldmat->bs2; 1904 a->mbs = oldmat->mbs; 1905 a->nbs = oldmat->nbs; 1906 a->Mbs = oldmat->Mbs; 1907 a->Nbs = oldmat->Nbs; 1908 1909 a->rstart = oldmat->rstart; 1910 a->rend = oldmat->rend; 1911 a->cstart = oldmat->cstart; 1912 a->cend = oldmat->cend; 1913 a->size = oldmat->size; 1914 a->rank = oldmat->rank; 1915 a->donotstash = oldmat->donotstash; 1916 a->roworiented = oldmat->roworiented; 1917 a->rowindices = 0; 1918 a->rowvalues = 0; 1919 a->getrowactive = PETSC_FALSE; 1920 a->barray = 0; 1921 a->rstart_bs = oldmat->rstart_bs; 1922 a->rend_bs = oldmat->rend_bs; 1923 a->cstart_bs = oldmat->cstart_bs; 1924 a->cend_bs = oldmat->cend_bs; 1925 1926 /* hash table stuff */ 1927 a->ht = 0; 1928 a->hd = 0; 1929 a->ht_size = 0; 1930 a->ht_flag = oldmat->ht_flag; 1931 a->ht_fact = oldmat->ht_fact; 1932 a->ht_total_ct = 0; 1933 a->ht_insert_ct = 0; 1934 1935 a->rowners = (int*)PetscMalloc(3*(a->size+2)*sizeof(int));CHKERRQ(ierr); 1936 PetscLogObjectMemory(mat,3*(a->size+2)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_MPISBAIJ)); 1937 a->cowners = a->rowners + a->size + 2; 1938 a->rowners_bs = a->cowners + a->size + 2; 1939 ierr = PetscMemcpy(a->rowners,oldmat->rowners,3*(a->size+2)*sizeof(int));CHKERRQ(ierr); 1940 ierr = MatStashCreate_Private(matin->comm,1,&mat->stash);CHKERRQ(ierr); 1941 ierr = MatStashCreate_Private(matin->comm,oldmat->bs,&mat->bstash);CHKERRQ(ierr); 1942 if (oldmat->colmap) { 1943 #if defined (PETSC_USE_CTABLE) 1944 ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr); 1945 #else 1946 a->colmap = (int*)PetscMalloc((a->Nbs)*sizeof(int));CHKERRQ(ierr); 1947 PetscLogObjectMemory(mat,(a->Nbs)*sizeof(int)); 1948 ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(int));CHKERRQ(ierr); 1949 #endif 1950 } else a->colmap = 0; 1951 if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) { 1952 ierr = PetscMalloc(len*sizeof(int),&( a->garray ));CHKERRQ(ierr); 1953 PetscLogObjectMemory(mat,len*sizeof(int)); 1954 ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(int));CHKERRQ(ierr); 1955 } else a->garray = 0; 1956 1957 ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr); 1958 PetscLogObjectParent(mat,a->lvec); 1959 ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr); 1960 1961 PetscLogObjectParent(mat,a->Mvctx); 1962 ierr = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr); 1963 PetscLogObjectParent(mat,a->A); 1964 ierr = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr); 1965 PetscLogObjectParent(mat,a->B); 1966 ierr = PetscFListDuplicate(mat->qlist,&matin->qlist);CHKERRQ(ierr); 1967 *newmat = mat; 1968 PetscFunctionReturn(0); 1969 } 1970 1971 #include "petscsys.h" 1972 1973 EXTERN_C_BEGIN 1974 #undef __FUNC__ 1975 #define __FUNC__ "MatLoad_MPISBAIJ" 1976 int MatLoad_MPISBAIJ(PetscViewer viewer,MatType type,Mat *newmat) 1977 { 1978 Mat A; 1979 int i,nz,ierr,j,rstart,rend,fd; 1980 Scalar *vals,*buf; 1981 MPI_Comm comm = ((PetscObject)viewer)->comm; 1982 MPI_Status status; 1983 int header[4],rank,size,*rowlengths = 0,M,N,m,*rowners,*browners,maxnz,*cols; 1984 int *locrowlens,*sndcounts = 0,*procsnz = 0,jj,*mycols,*ibuf; 1985 int tag = ((PetscObject)viewer)->tag,bs=1,Mbs,mbs,extra_rows; 1986 int *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount; 1987 int dcount,kmax,k,nzcount,tmp; 1988 1989 PetscFunctionBegin; 1990 ierr = PetscOptionsGetInt(PETSC_NULL,"-matload_block_size",&bs,PETSC_NULL);CHKERRQ(ierr); 1991 1992 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 1993 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 1994 if (!rank) { 1995 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 1996 ierr = PetscBinaryRead(fd,(char *)header,4,PETSC_INT);CHKERRQ(ierr); 1997 if (header[0] != MAT_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"not matrix object"); 1998 if (header[3] < 0) { 1999 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ"); 2000 } 2001 } 2002 2003 ierr = MPI_Bcast(header+1,3,MPI_INT,0,comm);CHKERRQ(ierr); 2004 M = header[1]; N = header[2]; 2005 2006 if (M != N) SETERRQ(PETSC_ERR_SUP,"Can only do square matrices"); 2007 2008 /* 2009 This code adds extra rows to make sure the number of rows is 2010 divisible by the blocksize 2011 */ 2012 Mbs = M/bs; 2013 extra_rows = bs - M + bs*(Mbs); 2014 if (extra_rows == bs) extra_rows = 0; 2015 else Mbs++; 2016 if (extra_rows &&!rank) { 2017 PetscLogInfo(0,"MatLoad_MPISBAIJ:Padding loaded matrix to match blocksize\n"); 2018 } 2019 2020 /* determine ownership of all rows */ 2021 mbs = Mbs/size + ((Mbs % size) > rank); 2022 m = mbs*bs; 2023 ierr = PetscMalloc(2*(size+2)*sizeof(int),& rowners );CHKERRQ(ierr); 2024 browners = rowners + size + 1; 2025 ierr = MPI_Allgather(&mbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr); 2026 rowners[0] = 0; 2027 for (i=2; i<=size; i++) rowners[i] += rowners[i-1]; 2028 for (i=0; i<=size; i++) browners[i] = rowners[i]*bs; 2029 rstart = rowners[rank]; 2030 rend = rowners[rank+1]; 2031 2032 /* distribute row lengths to all processors */ 2033 locrowlens = (int*)PetscMalloc((rend-rstart)*bs*sizeof(int));CHKERRQ(ierr); 2034 if (!rank) { 2035 ierr = PetscMalloc((M+extra_rows)*sizeof(int),& rowlengths );CHKERRQ(ierr); 2036 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 2037 for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1; 2038 ierr = PetscMalloc(size*sizeof(int),&( sndcounts ));CHKERRQ(ierr); 2039 for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i]; 2040 ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr); 2041 ierr = PetscFree(sndcounts);CHKERRQ(ierr); 2042 } else { 2043 ierr = MPI_Scatterv(0,0,0,MPI_INT,locrowlens,(rend-rstart)*bs,MPI_INT,0,comm);CHKERRQ(ierr); 2044 } 2045 2046 if (!rank) { /* procs[0] */ 2047 /* calculate the number of nonzeros on each processor */ 2048 ierr = PetscMalloc(size*sizeof(int),&( procsnz ));CHKERRQ(ierr); 2049 ierr = PetscMemzero(procsnz,size*sizeof(int));CHKERRQ(ierr); 2050 for (i=0; i<size; i++) { 2051 for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) { 2052 procsnz[i] += rowlengths[j]; 2053 } 2054 } 2055 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 2056 2057 /* determine max buffer needed and allocate it */ 2058 maxnz = 0; 2059 for (i=0; i<size; i++) { 2060 maxnz = PetscMax(maxnz,procsnz[i]); 2061 } 2062 ierr = PetscMalloc(maxnz*sizeof(int),&( cols ));CHKERRQ(ierr); 2063 2064 /* read in my part of the matrix column indices */ 2065 nz = procsnz[0]; 2066 ierr = PetscMalloc(nz*sizeof(int),&( ibuf ));CHKERRQ(ierr); 2067 mycols = ibuf; 2068 if (size == 1) nz -= extra_rows; 2069 ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr); 2070 if (size == 1) for (i=0; i< extra_rows; i++) { mycols[nz+i] = M+i; } 2071 2072 /* read in every ones (except the last) and ship off */ 2073 for (i=1; i<size-1; i++) { 2074 nz = procsnz[i]; 2075 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2076 ierr = MPI_Send(cols,nz,MPI_INT,i,tag,comm);CHKERRQ(ierr); 2077 } 2078 /* read in the stuff for the last proc */ 2079 if (size != 1) { 2080 nz = procsnz[size-1] - extra_rows; /* the extra rows are not on the disk */ 2081 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 2082 for (i=0; i<extra_rows; i++) cols[nz+i] = M+i; 2083 ierr = MPI_Send(cols,nz+extra_rows,MPI_INT,size-1,tag,comm);CHKERRQ(ierr); 2084 } 2085 ierr = PetscFree(cols);CHKERRQ(ierr); 2086 } else { /* procs[i], i>0 */ 2087 /* determine buffer space needed for message */ 2088 nz = 0; 2089 for (i=0; i<m; i++) { 2090 nz += locrowlens[i]; 2091 } 2092 ierr = PetscMalloc(nz*sizeof(int),&( ibuf ));CHKERRQ(ierr); 2093 mycols = ibuf; 2094 /* receive message of column indices*/ 2095 ierr = MPI_Recv(mycols,nz,MPI_INT,0,tag,comm,&status);CHKERRQ(ierr); 2096 ierr = MPI_Get_count(&status,MPI_INT,&maxnz);CHKERRQ(ierr); 2097 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2098 } 2099 2100 /* loop over local rows, determining number of off diagonal entries */ 2101 dlens = (int*)PetscMalloc(2*(rend-rstart+1)*sizeof(int));CHKERRQ(ierr); 2102 odlens = dlens + (rend-rstart); 2103 ierr = PetscMalloc(3*Mbs*sizeof(int),&( mask ));CHKERRQ(ierr); 2104 ierr = PetscMemzero(mask,3*Mbs*sizeof(int));CHKERRQ(ierr); 2105 masked1 = mask + Mbs; 2106 masked2 = masked1 + Mbs; 2107 rowcount = 0; nzcount = 0; 2108 for (i=0; i<mbs; i++) { 2109 dcount = 0; 2110 odcount = 0; 2111 for (j=0; j<bs; j++) { 2112 kmax = locrowlens[rowcount]; 2113 for (k=0; k<kmax; k++) { 2114 tmp = mycols[nzcount++]/bs; /* block col. index */ 2115 if (!mask[tmp]) { 2116 mask[tmp] = 1; 2117 if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */ 2118 else masked1[dcount++] = tmp; /* entry in diag portion */ 2119 } 2120 } 2121 rowcount++; 2122 } 2123 2124 dlens[i] = dcount; /* d_nzz[i] */ 2125 odlens[i] = odcount; /* o_nzz[i] */ 2126 2127 /* zero out the mask elements we set */ 2128 for (j=0; j<dcount; j++) mask[masked1[j]] = 0; 2129 for (j=0; j<odcount; j++) mask[masked2[j]] = 0; 2130 } 2131 2132 /* create our matrix */ 2133 ierr = MatCreateMPISBAIJ(comm,bs,m,m,PETSC_DETERMINE,PETSC_DETERMINE,0,dlens,0,odlens,newmat); 2134 CHKERRQ(ierr); 2135 A = *newmat; 2136 ierr = MatSetOption(A,MAT_COLUMNS_SORTED);CHKERRQ(ierr); 2137 2138 if (!rank) { 2139 ierr = PetscMalloc(maxnz*sizeof(Scalar),&( buf ));CHKERRQ(ierr); 2140 /* read in my part of the matrix numerical values */ 2141 nz = procsnz[0]; 2142 vals = buf; 2143 mycols = ibuf; 2144 if (size == 1) nz -= extra_rows; 2145 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2146 if (size == 1) for (i=0; i< extra_rows; i++) { vals[nz+i] = 1.0; } 2147 2148 /* insert into matrix */ 2149 jj = rstart*bs; 2150 for (i=0; i<m; i++) { 2151 ierr = MatSetValues(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2152 mycols += locrowlens[i]; 2153 vals += locrowlens[i]; 2154 jj++; 2155 } 2156 2157 /* read in other processors (except the last one) and ship out */ 2158 for (i=1; i<size-1; i++) { 2159 nz = procsnz[i]; 2160 vals = buf; 2161 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2162 ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,A->tag,comm);CHKERRQ(ierr); 2163 } 2164 /* the last proc */ 2165 if (size != 1){ 2166 nz = procsnz[i] - extra_rows; 2167 vals = buf; 2168 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 2169 for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0; 2170 ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,A->tag,comm);CHKERRQ(ierr); 2171 } 2172 ierr = PetscFree(procsnz);CHKERRQ(ierr); 2173 2174 } else { 2175 /* receive numeric values */ 2176 ierr = PetscMalloc(nz*sizeof(Scalar),&( buf ));CHKERRQ(ierr); 2177 2178 /* receive message of values*/ 2179 vals = buf; 2180 mycols = ibuf; 2181 ierr = MPI_Recv(vals,nz,MPIU_SCALAR,0,A->tag,comm,&status);CHKERRQ(ierr); 2182 ierr = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr); 2183 if (maxnz != nz) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file"); 2184 2185 /* insert into matrix */ 2186 jj = rstart*bs; 2187 for (i=0; i<m; i++) { 2188 ierr = MatSetValues_MPISBAIJ(A,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr); 2189 mycols += locrowlens[i]; 2190 vals += locrowlens[i]; 2191 jj++; 2192 } 2193 } 2194 2195 ierr = PetscFree(locrowlens);CHKERRQ(ierr); 2196 ierr = PetscFree(buf);CHKERRQ(ierr); 2197 ierr = PetscFree(ibuf);CHKERRQ(ierr); 2198 ierr = PetscFree(rowners);CHKERRQ(ierr); 2199 ierr = PetscFree(dlens);CHKERRQ(ierr); 2200 ierr = PetscFree(mask);CHKERRQ(ierr); 2201 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2202 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2203 PetscFunctionReturn(0); 2204 } 2205 EXTERN_C_END 2206 2207 #undef __FUNC__ 2208 #define __FUNC__ "MatMPISBAIJSetHashTableFactor" 2209 /*@ 2210 MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable. 2211 2212 Input Parameters: 2213 . mat - the matrix 2214 . fact - factor 2215 2216 Collective on Mat 2217 2218 Level: advanced 2219 2220 Notes: 2221 This can also be set by the command line option: -mat_use_hash_table fact 2222 2223 .keywords: matrix, hashtable, factor, HT 2224 2225 .seealso: MatSetOption() 2226 @*/ 2227 int MatMPISBAIJSetHashTableFactor(Mat mat,PetscReal fact) 2228 { 2229 PetscFunctionBegin; 2230 SETERRQ(1,"Function not yet written for SBAIJ format"); 2231 /* PetscFunctionReturn(0); */ 2232 } 2233 2234 #undef __FUNC__ 2235 #define __FUNC__ "MatGetRowMax_MPISBAIJ" 2236 int MatGetRowMax_MPISBAIJ(Mat A,Vec v) 2237 { 2238 Mat_MPISBAIJ *a = (Mat_MPISBAIJ*)A->data; 2239 Mat_SeqBAIJ *b = (Mat_SeqBAIJ*)(a->B)->data; 2240 PetscReal atmp; 2241 double *work,*svalues,*rvalues; 2242 int ierr,i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol; 2243 int rank,size,*rowners_bs,dest,count,source; 2244 Scalar *ba,*va; 2245 MPI_Status stat; 2246 2247 PetscFunctionBegin; 2248 ierr = MatGetRowMax(a->A,v);CHKERRQ(ierr); 2249 ierr = VecGetArray(v,&va);CHKERRQ(ierr); 2250 2251 ierr = MPI_Comm_size(PETSC_COMM_WORLD,&size);CHKERRA(ierr); 2252 ierr = MPI_Comm_rank(PETSC_COMM_WORLD,&rank);CHKERRA(ierr); 2253 2254 bs = a->bs; 2255 mbs = a->mbs; 2256 Mbs = a->Mbs; 2257 ba = b->a; 2258 bi = b->i; 2259 bj = b->j; 2260 /* 2261 PetscSynchronizedPrintf(PETSC_COMM_WORLD,"[%d] M: %d, bs: %d, mbs: %d \n",rank,bs*Mbs,bs,mbs); 2262 PetscSynchronizedFlush(PETSC_COMM_WORLD); 2263 */ 2264 2265 /* find ownerships */ 2266 rowners_bs = a->rowners_bs; 2267 /* 2268 if (!rank){ 2269 for (i=0; i<size+1; i++) PetscPrintf(PETSC_COMM_SELF," rowners_bs[%d]: %d\n",i,rowners_bs[i]); 2270 } 2271 */ 2272 2273 /* each proc creates an array to be distributed */ 2274 ierr = PetscMalloc(bs*Mbs*sizeof(PetscReal),&( work ));CHKERRQ(ierr); 2275 ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr); 2276 2277 /* row_max for B */ 2278 if (rank != size-1){ 2279 for (i=0; i<mbs; i++) { 2280 ncols = bi[1] - bi[0]; bi++; 2281 brow = bs*i; 2282 for (j=0; j<ncols; j++){ 2283 bcol = bs*(*bj); 2284 for (kcol=0; kcol<bs; kcol++){ 2285 col = bcol + kcol; /* local col index */ 2286 col += rowners_bs[rank+1]; /* global col index */ 2287 /* PetscPrintf(PETSC_COMM_SELF,"[%d], col: %d\n",rank,col); */ 2288 for (krow=0; krow<bs; krow++){ 2289 atmp = PetscAbsScalar(*ba); ba++; 2290 row = brow + krow; /* local row index */ 2291 /* printf("val[%d,%d]: %g\n",row,col,atmp); */ 2292 if (PetscRealPart(va[row]) < atmp) va[row] = atmp; 2293 if (work[col] < atmp) work[col] = atmp; 2294 } 2295 } 2296 bj++; 2297 } 2298 } 2299 /* 2300 PetscPrintf(PETSC_COMM_SELF,"[%d], work: ",rank); 2301 for (i=0; i<bs*Mbs; i++) PetscPrintf(PETSC_COMM_SELF,"%g ",work[i]); 2302 PetscPrintf(PETSC_COMM_SELF,"[%d]: \n"); 2303 */ 2304 2305 /* send values to its owners */ 2306 for (dest=rank+1; dest<size; dest++){ 2307 svalues = work + rowners_bs[dest]; 2308 count = rowners_bs[dest+1]-rowners_bs[dest]; 2309 ierr = MPI_Send(svalues,count,MPI_DOUBLE,dest,rank,PETSC_COMM_WORLD);CHKERRQ(ierr); 2310 /* 2311 PetscSynchronizedPrintf(PETSC_COMM_WORLD,"[%d] sends %d values to [%d]: %g, %g, %g, %g\n",rank,count,dest,svalues[0],svalues[1],svalues[2],svalues[3]); 2312 PetscSynchronizedFlush(PETSC_COMM_WORLD); 2313 */ 2314 } 2315 } 2316 2317 /* receive values */ 2318 if (rank){ 2319 rvalues = work; 2320 count = rowners_bs[rank+1]-rowners_bs[rank]; 2321 for (source=0; source<rank; source++){ 2322 ierr = MPI_Recv(rvalues,count,MPI_DOUBLE,MPI_ANY_SOURCE,MPI_ANY_TAG,PETSC_COMM_WORLD,&stat);CHKERRQ(ierr); 2323 /* process values */ 2324 for (i=0; i<count; i++){ 2325 if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i]; 2326 } 2327 /* 2328 PetscSynchronizedPrintf(PETSC_COMM_WORLD,"[%d] received %d values from [%d]: %g, %g, %g, %g \n",rank,count,stat.MPI_SOURCE,rvalues[0],rvalues[1],rvalues[2],rvalues[3]); 2329 PetscSynchronizedFlush(PETSC_COMM_WORLD); 2330 */ 2331 } 2332 } 2333 2334 ierr = VecRestoreArray(v,&va);CHKERRQ(ierr); 2335 ierr = PetscFree(work);CHKERRA(ierr); 2336 PetscFunctionReturn(0); 2337 } 2338